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        Analyst Perspectives

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        • for Topic: Ai And Machine Learning
        • Available Posts: 0

        The artificial intelligence (AI) landscape is undergoing dramatic transformation, with enterprises rapidly adapting to a world where AI is no longer just a possibility but a necessity. ISG Market Lensresearch of 300 enterprises shows that AI initiatives were the second largest category of IT spending for 2024, behind customer experience initiatives. Furthermore, enterprises plan to increase 2025 IT spending on AI initiatives by 5.7%, which is more than any other category and nearly three times...

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        Topics: Generative AI, AI & Technologies, AI and Machine Learning, Cloud Infrastructure

        The six costliest words in managing a finance department are, “We’ve always done it this way.” The record-to-report (R2R) cycle describes the process of finalizing and summarizing the financial activities of a business for a specific accounting periodtypically a month, quarter or fiscal year. It is important to note that R2R exclusively covers the activities between recording (keeping the books) and reporting (publishing financial statements and management accounts). It involves completing...

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        Topics: Office of Finance, ERP and Continuous Accounting, digital finance, Generative AI, Consolidate and Close Management, AI and Machine Learning

        One of the promised benefits of artificial intelligence (AI), Generative AI (GenAI) and agents is that they can make everyone their own financial and business analyst. It’s true that these technologies can make it possible for everyone to access once hard-to-reach data (with suitable permissions), unleash agents to assemble the data into useful tables and charts along with commentary describing results and highlighting underlying drivers of results, propose next best actions and use natural...

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        Topics: Office of Finance, Business Planning, ERP and Continuous Accounting, AI, AI and Machine Learning

        Enterprise Resource Planning (ERP) systems are comprehensive software platforms designed to integrate and manage all the core processes of an enterprise while recording transactions and their financial consequences to support the accounting and finance functions. ISG Software Research recently completed our Buyers Guide™ for ERP systems, designed to help enterprises that are replacing their existing ERP software to make the best choice, both in terms of the product’s performance as well as the...

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        Topics: Office of Finance, Continuous Planning, ERP and Continuous Accounting, AI and Machine Learning

        I recently completed the latest edition of our Business Planning Buyers Guide, which reviews and assesses the offerings of 14 providers of this software. One of the points that I look at is whether and to what extent the software provider offers out-of-the-box external data useful for forecasting, planning, analysis and evaluation. What I discovered is that the availability of this type of vital information is exceedingly slim.

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        Topics: Office of Finance, Analytics, Business Planning, AI and Machine Learning

        I recently attended Infor’s Velocity Summit, designed to showcase the latest versions of its CloudSuite ERP software. Also center stage were Infor’s advances in artificial intelligence and process mining as well as its environmental, social and governance application and supply chain optimization enhancements.

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        Topics: Office of Finance, ERP and Continuous Accounting, natural language processing, AI and Machine Learning, Continuous Supply Chain & ERP

        Artificial Intelligence and generative AI are beginning to change how enterprises do many things, especially planning and budgeting. This technology has the potential to significantly redefine the mission of the financial planning and analysis group. It will do so by substantially reducing the time spent on the purely mechanical aspects of day-to-day tasks. AI is also making it easier for executives and managers to rapidly forecast, plan and analyze to promote deeper situational awareness and...

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        Topics: Office of Finance, Analytics, Business Planning, Workforce Management, AI and Machine Learning

        Agents are all the rageand for a good reason. They are a way to automate work almost effortlessly so that repetitive and boring tasks get done with the least amount of effort on the part of the operator. In business, agents can be a boon for customer satisfaction and a way to improve worker productivity. They are alluring, with an almost unlimited number of potential use cases.

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        Topics: Office of Finance, Business Planning, ERP and Continuous Accounting, natural language processing, AI and Machine Learning, Digital Applications, Order-to-Cash

        In today's rapidly evolving technological landscape, artificial intelligence (AI) governance has emerged as a critical ingredient for successful AI deployments. It helps build trust in the results of AI models, it helps ensure compliance with regulations and it is necessary to meet internal governance requirements. Effective AI governance must encompass various dimensions, including data privacy, model drift, hallucinations, toxicity and perhaps most importantly, bias. Unfortunately, we expect...

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        Topics: AI, Analytics and Data, AI and Machine Learning

        As I’ve written recently, artificial intelligence governance is a concern for many enterprises. In our recent ISG Market Lens study on generative AI, 39% of participants cited data privacy and security among the biggest inhibitors to adopting AI. Nearly a third (32%) identified performance and quality (e.g., erroneous results), and an equal amount (32%) mentioned legal risk.

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        Topics: AI, Analytics and Data, AI and Machine Learning

        As I explained in our recent Buyers Guide for Data Platforms, the popularization of generative artificial intelligence (GenAI) has had a significant impact on the requirements for data platforms in the last 18 months. While there is an ongoing need for data platforms to support data warehousing workloads involving analytic reports and dashboards, there is increasing demand for analytic data platform providers to add dedicated functionality for data engineering, including the development,...

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        Topics: Analytics, natural language processing, AI and Machine Learning

        Prophix launched its Prophix One platform earlier this year. CFOs of midsize enterprises should take a look at it because it supports a more effective approach to finance and accounting operations in growing companies. It facilitates the transition of organizations that can no longer make do with work-arounds of existing systems to those with formal, controlled core processes that can be completed faster with reduced risk. The platform performs financial consolidation, account reconciliation...

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        Topics: Office of Finance, Business Planning, ERP and Continuous Accounting, AI and Machine Learning

        Enterprises face a bewildering level of choice in relation to data platforms, as evidenced by the number of software providers and products assessed in our recent Data Platforms Buyers Guide. There are numerous data platform providers and products to choose from, but also a diverse array of functional and architectural options. Is the workload primarily operational or analytic? Will it be deployed on-premises or in the cloud? Should it be distributed or centralized? Data warehouse or data...

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        Topics: Analytics and Data, AI and Machine Learning

        OneStream offers a platform designed to serve the needs of accounting and financial planning and analysis (FP&A) organizations. The software handles financial close and consolidation, planning and budgeting, analysis and reporting. OneStream recently held its annual user conference, Splash, in Las Vegas. In attending this meeting, my focus was on progress the company has made in the areas of predictive artificial intelligence (AI) and generative AI (GenAI) over the past year, since the...

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        Topics: Performance Management, Office of Finance, Business Planning, ERP and Continuous Accounting, AI and Machine Learning, Digital Applications

        I have written on multiple occasions about the increasing proportion of enterprises embracing the processing of streaming data and events alongside traditional batch-based data processing. I assert that, by 2026, more than three-quarters of enterprises’ standard information architectures will include streaming data and event processing, allowing enterprises to be more responsive and provide better customer experiences.

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        Topics: Streaming Data Events, Analytics and Data, AI and Machine Learning

        Having just completed our AI Platforms Buyers Guide assessment of 25 different software providers, I was surprised to see how few provided robust AI governance capabilities. As I’ve written previously, data governance has changed dramatically over the last decade, with nearly twice as many enterprises (71% v. 38%) implementing data governance policies during that time. With all this attention on data governance, I had expected AI platform software providers would recognize the needs of...

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        Topics: AI, Analytics and Data, AI and Machine Learning

        The artificial intelligence and machine learning landscape was profoundly altered by the emergence of generative AI into the mainstream consciousness during 2023. The widespread availability of GenAI models and cloud services has lowered the barriers to individuals and enterprises engaging with AI for various use cases, including generating content, querying data, writing code, preparing data for analysis, documenting data pipelines and using software products more effectively. The impact that...

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        Topics: Analytics and Data, AI and Machine Learning

        Embracing artificial intelligence technologies opens doors for innovation and efficiency. Alongside these opportunities, however, come risks. Threat actors are keenly aware of the potential impact of AI systems and are actively exploring ways to manipulate them. In this Analyst Perspective, I explore the world of adversarial machine-learning threats and provide practical guidance for securing AI systems.

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        Topics: Digital Technology, DevOps and Platforms, AI and Machine Learning

        ServiceNow is a global software provider that has developed a cloud computing platform that helps organizations manage digital workflows for enterprise operations. The provider uses its annual Knowledge user conference to educate customers and showcase product announcements. Ventana Research had the opportunity to attend the Knowledge 2024 event and provides this analyst perspective to summarize what transpired.

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        Topics: IT Service Management, Digital Technology, natural language processing, AI and Machine Learning

        Enterprises are embracing the potential for artificial intelligence (AI) to deliver improvements in productivity and efficiency. As they move from initial pilots and trial projects to deployment into production at scale, many are realizing the importance of agile and responsive data processes, as well as tools and platforms that facilitate data management, with the goal of improving trust in the data used to fuel analytics and AI. This has led to increased attention on the role of data...

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        Topics: data operations, Analytics and Data, AI and Machine Learning

        The emergence of generative artificial intelligence (GenAI) has significant implications at all levels of the technology stack, not least analytics and data products, which serve to support the development, training and deployment of GenAI models, and also stand to benefit from the advances in automation enabled by GenAI. The intersection of analytics and data and GenAI was a significant focus of the recent Google Cloud Next ’24 event. My colleague David Menninger has already outlined the key...

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        Topics: Analytics, AI, natural language processing, AI and Machine Learning

        I recently wrote about the development, testing and deployment of data pipelines as a fundamental accelerator of data-driven strategies as well as the importance of data orchestration to accelerate analytics and artificial intelligence. As I explained in the recent Data Observability Buyers Guide, data observability software is also a critical aspect of data-driven decision-making. Data observability addresses one of the most significant impediments to generating value from data by providing an...

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        Topics: Analytics, data operations, Analytics and Data, AI and Machine Learning

        Oracle held an industry analyst summit recently where the focus was on artificial intelligence (AI) and embedded AI. At the event, Oracle demonstrated progress in adding useful AI-enabled capabilities to its business applications, especially in finance and accounting, supply chain, HR and revenue management. To put this into context, across the software industry, AI is already at work in many finance-focused applications that are currently available, albeit often in limited release. We are in...

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        Topics: Office of Finance, Analytics, Business Planning, ERP and Continuous Accounting, AI and Machine Learning, Order-to-Cash

        The artificial intelligence (AI) market is exploding with activity, which is part of the reason we recently announced that we have dedicated an entire practice at Ventana Research to the topic. Large language models (LLMs) and generative AI (GenAI) have taken the AI world by storm. In fact, we assert that through 2026, one-half of all AI investments will be based on generative rather than predictive AI. My colleague Rob Kugel has written about how AI can improve productivity and benefit the...

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        Topics: AI, natural language processing, Analytics and Data, AI and Machine Learning

        I recently wrote about the development, testing and deployment of data pipelines as a fundamental accelerator of data-driven strategies. As I explained in the 2023 Data Orchestration Buyers Guide, today’s analytics environments require agile data pipelines that can traverse multiple data-processing locations and evolve with business needs.

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        Topics: Analytics, data operations, Analytics and Data, AI and Machine Learning

        I wrote recently about the role that data intelligence has in enabling enterprises to facilitate data democratization and the delivery of data as a product. Data intelligence provides a holistic view of how, when, and why data is produced and consumed across an enterprise, and by whom. This information can be used by data teams toensure business users and data analysts are provided with self-service access to data that is pertinent to their roles and requirements. Delivering data as a product...

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        Topics: Analytics, Data Ops, data operations, Analytics and Data, AI and Machine Learning

        The development, testing and deployment of data pipelines is a fundamental accelerator of data-driven strategies, enabling enterprises to extract data from the operational applications and data platforms designed to run the business and load, integrate and transform it into the analytic data platforms and tools used to analyze the business. As I explained in our recent Data Pipelines Buyers Guide, data pipelines are essential to generating intelligence from data. Healthy data pipelines are...

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        Topics: Analytics, data operations, Analytics and Data, AI and Machine Learning

        As enterprises seek to increase data-driven decision-making, many are investing in strategic data democratization initiatives to provide business users and data analysts with self-service access to data across the enterprise. Such access has long been a goal of many enterprises, but few have achieved it. Only 15% of participants in Ventana Research’s Analytics and Data Benchmark Research say their organization is very comfortable allowing business users to work with data that has not been...

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        Topics: Analytics, data operations, Analytics and Data, AI and Machine Learning

        In the technology industry, 2023 will be remembered as the year of generative artificial intelligence. Yes, the world was made aware of GenAI when ChatGPT was publicly launched in November of 2022, but few knew the impact it would have at that point in time. Since then, GenAI has taken the world by storm, with vendors applying the technology to make it easier to ask questions about data, write code (including SQL), prepare data for analyses, document data pipelines and use software products...

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        Topics: Artificial intelligence, Analytics and Data, AI and Machine Learning

        Artificial intelligence seems poised to change everything, although naturally a great deal of attention tends to be paid to the cool things it makes possible. AI can also make the humdrum less tedious and even transform the dullest of back-office operations into something more meaningful. For example, AI can take accounts receivable automation to the next level. 

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        Topics: Office of Finance, AI, AI and Machine Learning, Order-to-Cash

        Interest in artificial intelligence (AI) is exploding driven in large part by the widespread interest in generative AI. ISG’s AI Buyer Behavior Survey reported that more than 6 in 10 participants have at least one AI application in production. However, despite the ease with which individuals can use AI as a result of natural language processing, creating and managing AI models is still a challenge. First, there is a shortage of skills. Second, the process itself involves many parts, each of...

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        Topics: Data Science, AI, Analytics and Data, AI and Machine Learning

        Cloud computing has had an enormous impact on the analytics and data industry in recent decades, with the on-demand provisioning of computational resources providing new opportunities for enterprises to lower costs and increase efficiency. Two-thirds of participants in Ventana Research’s Data Lakes Dynamic Insightsresearch are using a cloud-based environment as the primary data platform for analytics. 

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        Topics: Analytics, AI, Analytics and Data, AI and Machine Learning

        I have previously written about the impact of intelligent operational applications on the requirements for data platforms. Intelligent applications are used to run the business but also deliver personalization, recommendations and other features generated by machine learning and artificial intelligence. As such, they require a combination of operational and analytic processing functionality. The emergence of these intelligent applications does not eradicate the need for separate analysis of...

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        Topics: Analytics, Artificial intelligence, Analytics and Data, AI and Machine Learning

        We live in an era of uncertainty, not unpredictability. Managing in uncertain times is always difficult, but tools are available to improve the odds for success by making it easier and faster to plan for contingencies and scenarios. Software makes it possible to manage ahead of any future event, connecting the tactical trees to the strategic forest. The purpose of planning is not just to create a plan: Enterprises spend time thinking ahead because it enables leadership teams, executives and...

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        Topics: Office of Finance, Continuous Planning, Data Management, Business Planning, data operations, AI and Machine Learning

        Unstructured data has been a significant factor in data lakes and analytics for some time. Twelve years ago, nearly a third of enterprises were working with large amounts of unstructured data. As I’ve pointed out previously, unstructured data is really a misnomer. The data is structured; it's just not structured into rows and columns that fit neatly into a relational table like much of the other information enterprises process. Consequently, it requires different skills, different technology...

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        Topics: Artificial intelligence, Computer Vision, Analytics and Data, AI and Machine Learning

        In recent years, many enterprises have migrated data platform workloads from on-premises infrastructure to cloud environments, attracted by the promised benefits of greater agility and lower costs. The scale of cloud data platform adoption is illustrated by Ventana Research’s Data Lakes Dynamic Insights research: For two-thirds (66%) of participants, the primary data platform used for analytics is cloud based. As the quantity and importance of the data platform workloads deployed in the cloud...

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        Topics: business intelligence, Cloud Computing, data operations, robotic automation, analytic data platforms, Analytics and Data, AI and Machine Learning

        Imagine a world where artificial intelligence (AI) seamlessly integrates into every facet of your business, only to subtly distort your data and skew your insights. This is the emerging challenge of AI hallucinations, a phenomenon where AI models perceive patterns or objects that do not exist or are beyond human detection.

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        Topics: Digital Technology, AI and Machine Learning

        Discussion about potential deployment locations for analytics and data workloads is often based on the assumption that, for enterprise workloads, there is a binary choice between on-premises data centers and public cloud. However, the low-latency performance or sovereignty characteristics of a significant and growing proportion of workloads make them better suited to data and analytics processing where data is generated rather than a centralized on-premises or public cloud environment. ...

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        Topics: Cloud Computing, Internet of Things, Data, Digital Technology, analytic data platforms, Analytics and Data, AI and Machine Learning

        The phrase ‘big data’ may have largely gone out of fashion, but the concept of storing and processing all relevant data continues to be important for enterprises seeking to be more data-driven. Doing so requires analytic data platforms capable of storing and processing data in multiple formats and data models. This will be an important focus for the forthcoming Data Platforms Buyer’s Guide 2024. 

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        Topics: Analytics, Business Intelligence, Data Management, Data, Digital Technology, data operations, Analytics and Data, AI and Machine Learning

        Ensuring digital effectiveness requires insights into how enterprises can provide the best outcomes through people, processes and technologies. Armed with those insights, business and technology investments can effectively innovate and streamline organizational processes.

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        Topics: Digital Technology, robotic automation, AI and Machine Learning

        I recently discussed how fashion has a surprisingly significant role to play in the data market as various architectural approaches to data storage and processing take turns enjoying a phase in the limelight. Pendulum swing is a theory of fashion that describes the periodic movement of trends between two extremes, such as short and long hemlines or skinny and baggy/flared trousers. Pendulum swing theory is similarly a factor in data technology trends, with an example being the oscillation...

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        Topics: Analytics, Cloud Computing, Data Management, Data, Digital Technology, data operations, Analytics and Data, AI and Machine Learning

        I recently articulated some of the reasons why IT teams can fail to deliver on the business requirements for data and analytics projects. This is an age-old and multifaceted problem that is not easily solved. Organizations have a role to play in alleviating the issue by ensuring that their business processes and project planning support a collaborative approach in which business and IT professionals work together. Data and analytics product vendors can also help by delivering products that are...

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        Topics: Cloud Computing, Data Governance, Data Management, Data, Digital Technology, Analytics and Data, AI and Machine Learning

        I previously wrote about the challenge facing distributed SQL database providers to avoid becoming pigeonholed as only being suitable for a niche set of requirements. Factors including performance, reliability, security and scalability provide a focal point for new vendors to differentiate from established providers and get a foot in the door with customer accounts. Expanding and retaining those accounts is not necessarily easy, however, especially as general-purpose data platform providers...

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        Topics: Analytics, Cloud Computing, Data, Digital Technology, Streaming Data Events, analytic data platforms, Analytics and Data, AI and Machine Learning

        Because artificial intelligence is top-of-mind, Workday spent a great deal of time on the topic at its recent Workday Rising annual user group meeting in San Francisco. It was front and center in the general sessions, in the announcements made at the event and in the product roadmaps.

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        Topics: Office of Finance, Business Planning, ERP and Continuous Accounting, AI and Machine Learning

        Alteryx was founded in 1997 and initially focused on analyzing demographic and geographically organized data. In 2006, the company released its eponymous product that established its direction for what the product is today. In 2017, it went public in an IPO on the NYSE. At the time of the IPO, Alteryx was focusing much of its marketing efforts on the data preparation market, particularly to support Tableau. Throughout this time though, Alteryx offered much more than data preparation. As a...

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        Topics: business intelligence, Analytics, data operations, Analytic Operations, Analytics and Data, AI and Machine Learning

        I previously described how Databricks had positioned its Lakehouse Platform as the basis for data engineering, data science and data warehousing. The lakehouse design pattern provides a flexible environment for storing and processing data from multiple enterprise applications and workloads for multiple use cases. I assert that by 2025, 8 in 10 current data lake adopters will invest in data lakehouse architecture to improve the business value generated from the accumulated data.

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        Topics: Analytics, Business Intelligence, Data Governance, Data Management, Data, Digital Technology, analytic data platforms, Analytics and Data, AI and Machine Learning

        I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research 2023 Augmented Analytics Buyers Guide is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to Analytics and Data vendors supporting...

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        Topics: Analytics, Augmented Analytics, AI and Machine Learning

        The 2023 Ventana Research Buyers Guide for Augmented Analytics research enables me to provide observations about how the market has advanced. 

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        Topics: Analytics, Augmented Analytics, AI and Machine Learning

        The data platforms market may appear to have little or nothing to do with haute couture, but it is one of the data sectors most strongly influenced by the fickle finger of fashion. In recent years, various architectural approaches to data storage and processing have enjoyed a phase in the limelight, including data warehouse, data mart, data hub, data lake, cloud data warehouse, object storage, data lakehouse, data fabric and data mesh. These approaches are often heralded as the next big thing,...

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        Topics: Cloud Computing, Data Governance, Data Management, Data, Digital Technology, data operations, Streaming Data Events, analytic data platforms, Analytics and Data, AI and Machine Learning

        Despite a focus on being data-driven, many organizations find that data and analytics projects fail to deliver on expectations. These initiatives can underwhelm for many reasons, because success requires a delicate balance of people, processes, information and technology. Small deviations from perfection in any of those factors can send projects off the rails.

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        Topics: Analytics, Business Intelligence, Data Management, Data, Digital Technology, data operations, AI and Machine Learning

        Organizations are continuously combining data from diverse and siloed sources for analytical, artificial intelligence and machine learning projects. As the volume of data grows, it becomes challenging for organizations to manage and keep current to extract valuable insights in a timely manner.

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        Topics: Analytics, Business Intelligence, AI and Machine Learning

        I have written before about the rising popularity of the data fabric approach for managing and governing data spread across distributed environments comprised of multiple data centers, systems and applications. I assert that by 2025, more than 6 in 10 organizations will adopt data fabric technologies to facilitate the management and processing of data across multiple data platforms and cloud environments. The data fabric approach is also proving attractive to vendors, including Microsoft, as a...

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        Topics: Analytics, Business Intelligence, Cloud Computing, Data Governance, Data Management, Data, Digital Technology, analytic data platforms, Analytics and Data, AI and Machine Learning

        Governance, risk management and compliance are essential tactics for a successful organization. Effective GRC practices help organizations achieve business objectives, mitigate risks and ensure compliance with laws and regulations. As a chief information officer or IT leader, it is important to evaluate new technologies and determine their impact on the business, including whether they fit within the scope of current GRC programs and processes.

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        Topics: Data Governance, AI and Machine Learning

        This title plays on the now-ancient meme from the 1990s: “On the internet, nobody knows you’re a dog,” which pointed to a challenge of anonymity posed by new technology. In this case, though, I’m using it to highlight an opportunity that generative artificial intelligence presents in streamlining routine business functions that require some level of individual skill and experience to handle. Ordinary contracts are just one example of work products that require humans to create, edit, analyze,...

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        Topics: Office of Finance, Digital Technology, robotic automation, AI and Machine Learning

        The world of human capital management (HCM) technology, and tech in general, is buzzing with excitement over the potential of generative artificial intelligence (GenAI). Startups, especially, are releasing software at seemingly breakneck speed, and larger vendors, specifically the platform providers, have been releasing their own net-new or enhanced features and functionality. We’ve all read that GenAI, and the practical application of large language models (LLMs), are the technological...

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        Topics: Human Capital Management, AI and Machine Learning

        The current market landscape of data and analytics is undergoing rapid evolution, presenting organizations with a wide array of challenges and opportunities. As data sources and warehouses steadily migrate to the cloud, a significant number of organizations still depend on conventional tools. This reliance on legacy systems hinders the seamless accessibility and adoption of analytics and business intelligence within business processes. Organizations are increasingly turning to embedded...

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        Topics: embedded analytics, Analytics, Business Intelligence, Streaming Analytics, AI and Machine Learning

        A century ago, the big breakthrough in telephones was the ability to dial your party’s number directly. Dialing became necessary when enough people had telephones to require a shift from people-assisted to fully automated connections. But direct dialing was only a local option – you still needed an operator to make long-distance calls. In the 1920s, commenting on their forecast for the expected growth of long-distance calling, the analysts at Bell Laboratories concluded that by midcentury, the...

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        Topics: Office of Finance, Analytics, Business Planning, AI and Machine Learning

        It is a mark of the rapid, current pace of development in artificial intelligence (AI) that machine learning (ML) models, until recently considered state of the art, are now routinely being referred to by developers and vendors as “traditional.” Generative AI, and large language models (LLMs) in particular, have taken the AI world by storm in the past year, automating and accelerating the development of content, including text, digital images, audio and video, as well as computer programs and...

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        Topics: Analytics, Business Intelligence, Cloud Computing, Data Governance, Data, Digital Technology, natural language processing, analytic data platforms, Analytics and Data, AI and Machine Learning

        As I have previously explained, we expect an increased demand for intelligent operational applications infused with the results of analytic processes, such as personalization and artificial intelligence-driven recommendations. These systems rely on the analysis of data in the operational data platform to accelerate worker decision-making or improve customer experience.

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        Topics: Analytics, Data, Digital Technology, Streaming Analytics, Streaming Data Events, Analytics and Data, AI and Machine Learning

        The six costliest words in managing a finance department are, “we’ve always done it this way.” Closing the books is the process of finalizing and summarizing the financial activities of a business for a specific accounting period (typically a month, quarter, or fiscal year). It involves completing various tasks to ensure that all revenue, expense, and other financial transactions are properly recorded, accounts are balanced, and financial statements are prepared. Accounting processes are...

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        Topics: Office of Finance, ERP and Continuous Accounting, AI and Machine Learning

        Intelligent automation is a powerful tool that can help the CIO and IT leaders optimize business processes and outcomes while reducing costs, risks and errors. Automation takes many forms, each with its own applications, benefits and limitations. In a previous perspective, I shared how technology helps organizations automate processes and enhance workflow efficiency. This perspective explains the various types of automation enabled by artificial intelligence technologies and their applications...

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        Topics: Digital Technology, robotic automation, AI and Machine Learning

        As we celebrate the first half of what seems to be the year of generative artificial intelligence, with an apparently unlimited discussion of use cases and bogeymen, my attention is turning to the very mundane question of costs. Specifically, how costs incurred – through investment and operation – will be distributed along the value chain and how this will affect the demand for AI ‒ by whom and for what purpose. It’s a question that needs asking even though, at this stage in the market’s...

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        Topics: Office of Finance, Continuous Planning, Business Planning, Enterprise Resource Planning, natural language processing, AI and Machine Learning, Continuous Supply Chain & ERP

        Automation uses technology to perform tasks or functions that would otherwise require human intervention or effort. Automation has existed for decades, and it takes many forms. It handles routine tasks, freeing time for knowledge workers to perform other activities that require creativity, subjectivity or empathy. Automation can also improve the quality, efficiency and consistency of business processes as well as enhance customer satisfaction and brand loyalty.

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        Topics: Digital Technology, robotic automation, AI and Machine Learning

        The publication of Ventana Research’s 2023 Operational Data Platforms Value Index earlier this year highlighted the importance of incorporating analytic processing into operational applications to deliver personalization and recommendations for workers, partners and customers. This importance is being accelerated by interest in generative AI, especially large language models. The emergence of intelligent applications has impacted the requirements for operational data platforms with the need to...

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        Topics: Analytics, Cloud Computing, Data, Digital Technology, analytic data platforms, Analytics and Data, AI and Machine Learning

        I recently attended Sage Software’s Partner Summit. Implementation partners account for most of the sales and implementation of finance and accounting applications designed for small and midsize businesses, so they are important to the success of the software vendor. These events are designed to inform partners of product enhancements and the product and technology roadmap as well as provide a perspective on market conditions and trends.

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        Topics: Office of Finance, Business Planning, ERP and Continuous Accounting, AI and Machine Learning

        A lot has been written about the definition of generative artificial intelligence (AI) and large language models (LLMs), though less has been written about the business considerations for an organization to evaluate adopting and implementing these technologies. And more importantly, does the technology align with the Office of the CIO objectives and the goals of the business? The value of generative AI software must be put into terms that all stakeholders can relate to. And organizations cannot...

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        Topics: Digital Technology, natural language processing, Collaborative & Conversational Computing, AI and Machine Learning

        The Office of Finance can be compared to a numbers factory where the main raw material, data, is transformed into financial statements, management accounting, analyses, forecasts, budgets, regulatory filings, tax returns and all kinds of reports. Data is the strategic raw material of the finance and accounting department. It is the key ingredient in every sale and purchase as well as every transaction of any description. Quality control is essential to achieving high standards of output in any...

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        Topics: Office of Finance, embedded analytics, Analytics, Business Intelligence, Data Management, Business Planning, ERP and Continuous Accounting, data operations, analytic data platforms, AI and Machine Learning

        The data and analytics sector rightly places great importance on data quality: Almost two-thirds (64%) of participants in Ventana Research’s Analytics and Data Benchmark Research cite reviewing data for quality and consistency issues as the most time-consuming task in analyzing data. Data and analytics vendors would not recommend that customers use tools known to have data quality problems. It is somewhat surprising, therefore, that data and analytics vendors are rushing to encourage customers...

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        Topics: Analytics, Data Governance, Data Management, Data, Digital Technology, natural language processing, Analytics and Data, AI and Machine Learning

        Artificial intelligence (AI) has evolved from a highly specialized niche technology to a worldwide phenomenon. Nearly 9 in 10 organizations use or plan to adopt AI technology. Several factors have contributed to this evolution. First, the amount of data they can collect and store has increased dramatically while the cost of analyzing these large amounts of data has decreased dramatically. Data-driven organizations need to process data in real time which requires AI. In addition, analytics...

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        Topics: Analytics, Digital Technology, natural language processing, Analytics and Data, AI and Machine Learning

        Artificial intelligence (AI) has become ubiquitous in discussions of contact center technology. Vendors are rushing to incorporate it into platforms and applications. And end users have understandably mixed feelings about where it makes sense to use and what its impacts will be. No one should be surprised that AI has arrived, especially for customer support: Software companies have been working on customer experience (CX)- -related AI applications for many years, and the fruits of those efforts...

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        Topics: Customer Experience, Contact Center, agent management, AI and Machine Learning

        The data platforms market has traditionally been divided between products specifically designed to support operational or analytic workloads, with other market segments having emerged in recent years for data platforms targeted specifically at data science and machine learning (ML), as well as real-time analytics. More recently, we have seen vendor strategies evolving to provide a more consolidated approach, with data platforms designed to address a combination of analytics and data science, as...

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        Topics: Analytics, Business Intelligence, Cloud Computing, Data, Digital Technology, analytic data platforms, Analytics and Data, AI and Machine Learning

        OneStream offers a platform designed to serve the needs of accounting and financial planning and analysis organizations. The software handles financial close and consolidation, planning and budgeting, analysis and reporting. The most notable part of the company’s presentations at its annual user group meeting – Splash – was the strategy and roadmap for its two artificial intelligence initiatives, Sensible ML and Sensible GPT. The former, unveiled last year, is a platform approach to applying...

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        Topics: Office of Finance, AI and Machine Learning

        Generative AI is a class of artificial intelligence used to generate new, seemingly real content. Broadly speaking, AI has traditionally been used to identify patterns in data and apply those patterns to categorize and predict behaviors. For instance, it can organize customers into groups (or clusters) with similar characteristics, or predict which customers are most likely to respond to certain offers.

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        Topics: Analytics, Digital Technology, AI and Machine Learning

        Early last December, just before ChatGPT became the new, bright, shiny object, The Economist magazine ran a story proclaiming that we had finally arrived at the age of boring artificial intelligence (AI). From my perspective, it’s unfortunate that didn’t last and that AI has been relegated back to the buzzword league. AI will be an increasingly important feature of business software through the end of this decade. Ventana Research asserts that by 2026, almost all vendors of software designed...

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        Topics: Office of Finance, Business Intelligence, Business Planning, Enterprise Resource Planning, ERP and Continuous Accounting, natural language processing, continuous supply chain, AI and Machine Learning

        Organizations are continuously searching for new business opportunities hidden in their data. They are using various technologies including artificial intelligence and machine learning (AI/ML) to uncover granular insights that can support decision-making. Existing tools and dashboards are effective for observing standard metrics; however, they do not address follow-up questions, such as why things are happening or how those events impact performance. Organizations also struggle to derive...

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        Topics: Analytics, Business Intelligence, natural language processing, AI and Machine Learning

        We live in a time of uncertainty, not unpredictability. Managing an organization in uncertain times is always hard, but tools are available to improve the odds for success by making it easier and faster to plan for contingencies and scenarios. Software makes it possible to quickly consider the impact of a range of events or assumptions and devise a set of plans to deal with them. Dedicated planning and budgeting software has been around for decades but is about to become all the more useful as...

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        Topics: Office of Finance, Data Management, Business Planning, AI and Machine Learning

        I’ve previously written about the analytics continuum, which spans a range of capabilities including reporting, visualization, planning, real-time processes, natural language processing, artificial intelligence and machine learning. I’ve also written about the analysis that goes into making intelligent decisions with decision intelligence. In this perspective, I’d like to focus on one end of the analytics continuum, which I’ll label advanced analytics.

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        Topics: Analytics, Digital Technology, Analytics and Data, AI and Machine Learning

        Despite the emphasis on organizations being more data-driven and making an increasing proportion of business decisions based on data and analytics, it remains the case that some of the most fundamental questions about an organization are difficult to answer using data and analytics. Ostensibly simple questions such as, “how many customers does the organization have?” can be fiendishly difficult to answer, especially for organizations with multiple business entities, regions, departments and...

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        Topics: Cloud Computing, Data Management, Data, data operations, Analytics and Data, AI and Machine Learning

        Markets have been more volatile than ever. It creates a need for decision makers to utilize technologies such as artificial intelligence and machine learning (AI/ML) to better understand the external factors that impact their business. By identifying these factors, organizations can better plan for changing market environments and seize market opportunities. However, manual modeling is a time-consuming process and results in a limited number of models and tests. Also, updating those models is...

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        Topics: embedded analytics, Analytics, Business Intelligence, AI and Machine Learning

        Ventana Research recently announced its 2023 research agenda for the Office of Revenue, continuing the guidance we’ve offered for nearly two decades to help organizations realize their optimal value from applying technology to improve business outcomes. Chief Sales and Revenue Officers face an imperative to manage their sales and revenue organizations, but they don’t always have the guidance they need to embrace technology to achieve the best possible outcomes. As we look forward to 2023, we...

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        Topics: Sales, Analytics, Internet of Things, Data, Sales Performance Management, Digital Technology, Digital Commerce, Conversational Computing, mobile computing, Subscription Management, extended reality, intelligent sales, partner management, AI and Machine Learning

        Ventana Research recently announced its Market Agenda in the expertise area of Customer Experience. CX has emerged as a way for organizations to demonstrate value and stand out in the marketplace. The technology underlying modern CX is transitioning from tools that are based on communication to those centered on data analysis and process automation. This allows organizations to build great experiences and reap the benefits in customer loyalty and value. It also forces companies to reckon with...

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        Topics: Customer Experience, Voice of the Customer, CEM, Self-service, Analytics, Contact Center, agent management, AI and Machine Learning

        I’m proud to share Ventana Research’s 2023 Market Agenda for Digital Technology. Our focus in this agenda is to deliver expertise to help organizations prioritize technology investments that improve customer, partner and workforce experiences while also increasing organizational effectiveness and agility.

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        Topics: Analytics, Cloud Computing, Internet of Things, Data, Digital Technology, blockchain, mobile computing, extended reality, robotic automation, Collaborative & Conversational Computing, AI and Machine Learning

        Vertical strategies for enterprise resource planning systems are not new. They emerged more than two decades ago as vendors looked for ways to reduce costs and shorten time-to-value in a software category that was notorious for high costs and extended timelines. A vertical-plus strategy – the plus means it’s a platform, not just an application – takes advantage of recently available technology to extend the ease of implementation and maintenance of the system by having deeper integration with...

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        Topics: Office of Finance, Cloud Computing, ERP and Continuous Accounting, AI and Machine Learning

        In today’s organization, the myriad of analytics and permutations of dashboards challenge workers’ ability to take contextual actions efficiently. Unfortunately, conventional wisdom for investing in analytics does not recognize the benefits of empowering the workforce to understand the situation, examine options and work together to make the best possible decision.

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        Topics: business intelligence, Analytics, Data, Digital Technology, analytic data platforms, Analytics and Data, AI and Machine Learning

        Organizations conduct data analysis in many ways. The process can include multiple spreadsheets, applications, desktop tools, disparate data systems, data warehouses and analytics solutions. This creates difficulties for management to provide and maintain updated information across multiple departments. Our Analytics and Data Benchmark Research shows that organizations face a variety of challenges with analytics and business intelligence. One-third of participants find it difficult to integrate...

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        Topics: embedded analytics, Analytics, Business Intelligence, natural language processing, AI and Machine Learning

        For far too long, business intelligence technologies have left the rest of the exercise to the reader. Many of these tools do an excellent job providing information in an interactive way that lets organizations dive into the data and learn a lot about what has happened across all aspects of the business. More recently, many of these tools have added augmented intelligence capabilities that help explain why things happened. But rarely did any of these tools provide information about what to do...

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        Topics: Analytics, Business Intelligence, Digital Technology, Analytics and Data, AI and Machine Learning

        The shift from on-premises server infrastructure to cloud-based and software-as-a-service (SaaS) models has had a profound impact on the data and analytics architecture of many organizations in recent years. More than one-half of participants (59%) in Ventana Research’s Analytics and Data Benchmark research are deploying data and analytics workloads in the cloud, and a further 30% plan to do so. Customer demand for cloud-based consumption models has also had a significant impact on the products...

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        Topics: Business Intelligence, Cloud Computing, Data Management, Data, natural language processing, data operations, analytic data platforms, Analytics and Data, AI and Machine Learning

        Ventana Research uses the term “data pantry” to describe a method of data storage (and the technology and process blueprint for its construction) created for a specific set of users and use cases in business-focused software. It’s a pantry because all the data one needs is readily available and easily accessible, with labels that are immediately recognized and understood by the users of the application. In tech speak, this means the semantic layer is optimized for the intended audience. It is...

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        Topics: Continuous Planning, Business Intelligence, Data Management, Business Planning, Data, Financial Performance Management, Enterprise Resource Planning, continuous supply chain, data operations, Streaming Data Events, Analytics and Data, AI and Machine Learning

        In previous perspectives in this series, I’ve discussed some of the realities of cloud computing including costs, hybrid and multi-cloud configurations and business continuity. This perspective examines the realities of security and regulatory concerns associated with cloud computing. These issues are often cited by our research participants as reasons they are not embracing the cloud. To be fair, the majority of our research participants are embracing the cloud. However, among those that have...

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        Topics: Analytics, Business Intelligence, Cloud Computing, Data Governance, Digital Technology, Analytics and Data, AI and Machine Learning

        Recently, I suggested you need to “mind the gap” between data and analytics. This perspective addresses another gap — the gap in skills between business intelligence (BI) and artificial intelligence/machine learning (AI/ML).

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        Topics: Analytics, Business Intelligence, Digital Technology, Analytics and Data, AI and Machine Learning

        One of the most significant considerations when choosing an analytic data platform is performance. As organizations compete to benefit most from being data-driven, the lower the time to insight the better. As data practitioners have learnt over time, however, lowering time to insight is about more than just high-performance queries. There are opportunities to improve time to insight throughout the analytics life cycle, which starts with data ingestion and integration, includes data preparation...

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        Topics: Business Intelligence, Data, data operations, analytic data platforms, AI and Machine Learning

        Embedded business intelligence (BI) continues to transform the business landscape, enabling organizations to quickly interpret data and convert it into actionable insights. It allows organizations to extract information in real time and answer wide-ranging business questions. Embedding analytics helps tackle the issue of extracting information from data which is a time-consuming process. Our research shows organizations spend more time cleaning and optimizing data for analysis rather than...

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        Topics: embedded analytics, Analytics, Business Intelligence, natural language processing, Streaming Analytics, AI and Machine Learning

        In today’s data-driven world, organizations need real-time access to up-to-date, high-quality data and analysis to keep pace with changing market dynamics and make better strategic decisions. By mining meaningful insights from enterprise data quickly, they gain a competitive advantage in the market. Yet, organizations face a multitude of challenges when transitioning into an analytics-driven enterprise. Our Analytics and Data Benchmark Research shows that more than one-quarter of organizations...

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        Topics: embedded analytics, Analytics, Business Intelligence, IBM, IBM Watson, AI and Machine Learning

        Almost all organizations are investing in data science, or planning to, as they seek to encourage experimentation and exploration to identify new business challenges and opportunities as part of the drive toward creating a more data-driven culture. My colleague, David Menninger, has written about how organizations using artificial intelligence and machine learning (AI/ML) report gaining competitive advantage, improving customer experiences, responding faster to opportunities and threats, and...

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        Topics: Data Governance, Data Management, Data, data operations, analytic data platforms, Analytics and Data, AI and Machine Learning

        The starting point of an era is never precise and rarely conforms to neat calendar delineations. For example, the start of the 20th century is associated with the outbreak of war in 1914. So I expect that decades from now, the consensus will hold that what became known as the 21st century began in the year 2020, with the pandemic serving as a catalyst that accelerated already existing trends and forced changes to prevailing norms and practices. This and other disruptive events that have...

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        Topics: Office of Finance, Business Intelligence, Business Planning, Financial Performance Management, AI and Machine Learning

        IBM Planning Analytics with Watson is a comprehensive, cloud-based business planning application that supports what Ventana Research calls integrated business planning. We coined this term in 2007 to describe a high-participation approach to business planning that integrates strategy, operations and finance. Our Next Generation Business Planning Benchmark Research demonstrated the value of IBP: Organizations that link planning processes get better results. Sixty-six percent of organizations...

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        Topics: Predictive Analytics, Office of Finance, embedded analytics, Business Intelligence, Business Planning, Financial Performance Management, Watson, Digital transformation, AI and Machine Learning

        I have previously written about growing interest in the data lakehouse as one of the design patterns for delivering hydroanalytics analysis of data in a data lake. Many organizations have invested in data lakes as a relatively inexpensive way of storing large volumes of data from multiple enterprise applications and workloads, especially semi- and unstructured data that is unsuitable for storing and processing in a data warehouse. However, early data lake projects lacked structured data...

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        Topics: Business Intelligence, Data Governance, Data Management, Data, Streaming Data Events, analytic data platforms, AI and Machine Learning

        I have written recently about the similarities and differences between data mesh and data fabric. The two are potentially complementary. Data mesh is an organizational and cultural approach to data ownership, access and governance. Data fabric is a technical approach to automating data management and data governance in a distributed architecture. There are various definitions of data fabric, but key elements include a data catalog for metadata-driven data governance and self-service, agile data...

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        Topics: Business Intelligence, Cloud Computing, Data Governance, Data Management, Data, data operations, AI and Machine Learning

        I have written a few times in recent months about vendors offering functionality that addresses data orchestration. This is a concept that has been growing in popularity in the past five years amid the rise of Data Operations (DataOps), which describes more agile approaches to data integration and data management. In a nutshell, data orchestration is the process of combining data from multiple operational data sources and preparing and transforming it for analysis. To those unfamiliar with the...

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        Topics: Data Management, Data, data operations, Analytics and Data, AI and Machine Learning

        Artificial intelligence and machine learning are valuable to data and analytics activities. Our research shows that organizations using AI/ML report gaining competitive advantage, improving customer experiences, responding faster to opportunities and threats and improving the bottom line with increased sales and lower costs. No wonder nearly 9 in 10 (87%) research participants report using AI/ML or planning to do so.

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        Topics: Analytics, AI and Machine Learning

        Ventana Research’s Data Lakes Dynamics Insights research illustrates that while data lakes are fulfilling their promise of enabling organizations to economically store and process large volumes of raw data, data lake environments continue to evolve. Data lakes were initially based primarily on Apache Hadoop deployed on-premises but are now increasingly based on cloud object storage. Adopters are also shifting from data lakes based on homegrown scripts and code to open standards and open...

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        Topics: Business Intelligence, Data Governance, Data Management, Data, data operations, Streaming Data Events, analytic data platforms, Analytics and Data, AI and Machine Learning

        As I recently pointed out, process mining has emerged as a pivotal technology for data-driven organizations to discover, monitor and improve processes through use of real-time event data, transactional data and log files. With recent advancements, process mining has become more efficient at discovering insights in complex processes using algorithms and visualizations. Organizations use it to better understand the current state of systems and business processes. It is also used to enable ...

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        Topics: Analytics, Business Intelligence, Process Mining, Streaming Analytics, AI and Machine Learning

        Earlier this year I described the growing use-cases for hybrid data processing. Although it is anticipated that the majority of database workloads will continue to be served by specialist data platforms targeting operational and analytic workloads respectively, there is increased demand for intelligent operational applications infused with the results of analytic processes, such as personalization and artificial intelligence-driven recommendations. There are multiple data platform approaches to...

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        Topics: Business Intelligence, Cloud Computing, Data, Streaming Data Events, analytic data platforms, AI and Machine Learning

        A predictive finance department is one that can command technology to be more forward-looking and action-oriented while still fulfilling its core role of handling the financial elements of its organization including accounting, treasury and corporate finance. Beyond just automating rote tasks, technology also facilitates a shift toward becoming a predictive finance organization. Greater amounts of information, now available in near real time, and the increasing use of artificial intelligence...

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        Topics: Office of Finance, Business Intelligence, Data Management, Business Planning, Financial Performance Management, ERP and Continuous Accounting, AI and Machine Learning

        Process mining is defined as the analysis of application telemetry including log files, transaction data and other instrumentation to understand and improve operational processes. Log data provides an abundance of information about what operations are occurring, the sequences involved in the processes, how long the processes are taking and whether or not the processes are completed successfully. As computing power has increased and storage costs have decreased, the economics of collecting and...

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        Topics: Analytics, Business Intelligence, Process Mining, AI and Machine Learning

        Organizations are collecting data from multiple data sources and a variety of systems to enrich their analytics and business intelligence (BI). But collecting data is only half of the equation. As the data grows, it becomes challenging to find the right data at the right time. Many organizations can’t take full advantage of their data lakes because they don’t know what data actually exists. Also, there are more regulations and compliance requirements than ever before. It is critical for...

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        Topics: Business Intelligence, Data Governance, Data Management, data operations, AI and Machine Learning

        Kinaxis recently announced it has acquired a Netherlands-based company, MPO, a cloud-based software offering that orchestrates multiparty supply chain execution. The combination is designed to enable Kinaxis to extend its concurrent planning platform to handle core elements of supply chain execution. Kinaxis acquired all the shares of MPO for approximately US$45 million, with some of the final consideration dependent on performance. MPO will continue to operate as a standalone business, but...

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        Topics: Business Intelligence, Business Planning, Operations & Supply Chain, Enterprise Resource Planning, continuous supply chain, AI and Machine Learning

        I have written about vendor efforts to use artificial intelligence (AI) and advanced analytics in their applications targeted at sales and revenue teams to improve focus and prioritize activities, both for pipeline management as well as individual opportunities. Since then, vendors have continued to innovate, and there have been more releases showcasing efforts to aid sales and revenue. And with this continuing innovation, we believe that by 2026, two-thirds of revenue leaders will begin...

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        Topics: AI and Machine Learning

        Business intelligence has evolved. It now includes a spectrum of analytics, one of the most promising of which has been described as augmented intelligence. Some organizations have used the term to describe the practical reality that artificial intelligence with machine learning is not replacing human intelligence, but augmenting it. The term also represents the application of AI/ML to make business intelligence and analytics tools more powerful and easier to use. It’s this latter usage that I...

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        Topics: Analytics, Business Intelligence, natural language processing, Collaborative & Conversational Computing, Analytics and Data, AI and Machine Learning

        Organizations do not live in a vacuum and things happening outside their walls have a direct impact on how they perform. So, it is essential for them to incorporate external data in their forecasting, planning and budgeting, especially for predictive analytics and machine learning (ML) to support artificial intelligence (AI). I use the term external data to include any information about the world outside an organization (including economic and market statistics), competitors (such as pricing...

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        Topics: Office of Finance, Business Planning, Financial Performance Management, AI and Machine Learning

        Zoho presented analysts with a deep look at its strategy and roadmap at its July analyst conference, describing how it intends to meld its many business applications together through integration at the level of the platform. The company, which is privately owned and funded, has generally sought to build its own tools rather than buy or partner. This approach has allowed the firm to create a suite of tightly linked tools that share a common interface.

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        Topics: Customer Experience, Voice of the Customer, Data, AI and Machine Learning

        Organizations are managing and analyzing large datasets every day, identifying patterns and generating insights to inform decisions. This can provide numerous benefits for an organization, such as improved operational efficiency, cost optimization, fraud detection, competitive advantage and enhanced business processes. By bringing the right, actionable data to the right user, organizations can potentially speed up processes and make more effective operational decisions.

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        Topics: embedded analytics, Business Intelligence, Internet of Things, Streaming Analytics, AI and Machine Learning

        The analytics and business intelligence market landscape continues to grow as more organizations seek robust tools and capabilities to visualize and better understand data. BI systems are used to perform data analysis, identify market trends and opportunities and streamline business processes. They can collect and combine data from internal and external systems to present a holistic view.

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        Topics: Analytics, Business Intelligence, Data Governance, Data Management, Analytics and Data, AI and Machine Learning

        Anaplan offers a cloud-based business planning platform that incorporates a modeling and calculation engine. The tool makes it relatively easy to add or expand the scope of plans that can be connected and monitored on a single platform. This Integrated Business Planning (IBP) approach enables organizations to use the software for financial planning or budgeting, sales, supply chain, workforce, marketing and IT planning. These are the types of plans in which companies often need to create models...

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        Topics: Office of Finance, Continuous Planning, Business Intelligence, Business Planning, Financial Performance Management, continuous supply chain, AI and Machine Learning

        I recently explained how emerging application requirements were expanding the range of use cases for NoSQL databases, increasing adoption based on the availability of enhanced functionality. These intelligent applications require a close relationship between operational data platforms and the output of data science and machine learning projects. This ensures that machine learning and predictive analytics initiatives are not only developed and trained based on the relationships inherent in...

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        Topics: Business Intelligence, Data, analytic data platforms, AI and Machine Learning

        I often use the term “analytics” to refer to a broad set of capabilities, deliberately broader than business intelligence. In this Perspective, I’d like to share what decision-makers should consider as they evaluate the range of analytics requirements for their organization.

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        Topics: Business Intelligence, natural language processing, Streaming Analytics, Analytics and Data, AI and Machine Learning

        Organizations are collecting vast amounts of data every day, utilizing business intelligence software and data visualization to gain insights and identify patterns and errors in the data. Making sense of these patterns can enable an organization to gain an edge in the marketplace and plan more strategically.

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        Topics: embedded analytics, Analytics, Business Intelligence, AI and Machine Learning

        When joining Ventana Research, I noted that the need to be more data-driven has become a mantra among large and small organizations alike. Data-driven organizations stand to gain competitive advantage, responding faster to worker and customer demands for more innovative, data-rich applications and personalized experiences. Being data-driven is clearly something to aspire to. However, it is also a somewhat vague concept without clear definition. We know data-driven organizations when we see them...

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        Topics: embedded analytics, Analytics, Business Intelligence, Data Governance, Data Integration, Data, Digital Technology, natural language processing, data lakes, data operations, Streaming Analytics, Streaming Data Events, Analytics and Data, AI and Machine Learning

        OneStream offers a platform designed to serve the needs of accounting and financial planning and analysis organizations. The software handles financial close and consolidation, planning and budgeting, analysis and reporting. For me, the most significant announcement at the company’s recent user conference was the unveiling of its Sensible ML (Machine Learning) offering, which is in limited general release. I’ve commented on the importance of artificial intelligence in business applications, and...

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        Topics: Business Planning, Financial Performance Management, ERP and Continuous Accounting, AI and Machine Learning

        I recently wrote about the growing range of use cases for which NoSQL databases can be considered, given increased breadth and depth of functionality available from providers of the various non-relational data platforms. As I noted, one category of NoSQL databases — graph databases — are inherently suitable for use cases that rely on relationships, such as social media, fraud detection and recommendation engines, since the graph data model represents the entities and values and also the...

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        Topics: business intelligence, Analytics, Cloud Computing, Data, Digital Technology, Analytics and Data, AI and Machine Learning

        A few years ago – somewhat tongue in cheek – I began using the term “data pantry” to describe a type of data store that’s part of a business application platform, created for a specific set of users and use cases. It’s a data pantry because, unlike a general-purpose data store such as a data warehouse, everything the user needs is readily available and easily accessible, with labels that are immediately recognized and understood.

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        Topics: Data Management, Business Planning, Financial Performance Management, ERP and Continuous Accounting, AI and Machine Learning

        Organizations are continuously increasing the use of analytics and business intelligence to turn data into meaningful and actionable insights. Our Analytics and Data Benchmark Research shows some of the benefits of using analytics: Improved efficiency in business processes, improved communication and gaining a competitive edge in the market top the list. With a unified BI system, organizations can have a comprehensive view of all organizational data to better manage processes and identify...

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        Topics: business intelligence, embedded analytics, Data Governance, Data Management, natural language processing, data operations, Streaming Analytics, AI and Machine Learning

        I previously described the concept of hydroanalytic data platforms, which combine the structured data processing and analytics acceleration capabilities associated with data warehousing with the low-cost and multi-structured data storage advantages of the data lake. One of the key enablers of this approach is interactive SQL query engine functionality, which facilitates the use of existing business intelligence (BI) and data science tools to analyze data in data lakes. Interactive SQL query...

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        Topics: Analytics, Business Intelligence, Cloud Computing, Data, Digital Technology, data lakes, data operations, Analytics and Data, AI and Machine Learning

        I’ve never been a fan of talking about semantic models because most of the workforce probably doesn’t understand what they are, or doesn’t recognize them by name. But the findings in our recent Analytics and Data Benchmark Research have changed my mind. The research shows how important a semantic model can be to the success of data and analytics processes. Organizations that have successfully implemented a semantic model are more than twice as likely to report satisfaction with analytics (77%)...

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        Topics: Business Intelligence, Data Management, data operations, Analytics and Data, AI and Machine Learning

        Artificial intelligence using machine learning has passed through the bright, shiny object stage and software vendors are well into the process of making the concept a reality in their offerings. Ventana Research defines AI as the use of technology to process information in much the way humans do, including improving accuracy in recommendations, actions and conclusions as more data is received. I like the alternative term “augmented intelligence” because it emphasizes that these systems enhance...

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        Topics: Planning, Machine Learning, Budgeting, Business Planning, Financial Performance Management, forecasting, AI and Machine Learning

        I recently wrote about the potential benefits of data mesh. As I noted, data mesh is not a product that can be acquired, or even a technical architecture that can be built. It’s an organizational and cultural approach to data ownership, access and governance. While the concept of data mesh is agnostic to the technology used to implement it, technology is clearly an enabler for data mesh. For many organizations, new technological investment and evolution will be required to facilitate adoption...

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        Topics: Analytics, Business Intelligence, Data Governance, Data Integration, Data, data operations, Streaming Data Events, AI and Machine Learning

        I recently described the use cases driving interest in hybrid data processing capabilities that enable analysis of data in an operational data platform without impacting operational application performance or requiring data to be extracted to an external analytic data platform. Hybrid data processing functionality is becoming increasingly attractive to aid the development of intelligent applications infused with personalization and artificial intelligence-driven recommendations. These...

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        Topics: Analytics, Business Intelligence, Cloud Computing, Data, Digital Technology, Analytics and Data, AI and Machine Learning

        There is a fundamental flaw in information technology, or at least in the way it is most commonly delivered. Most technology systems are developed under the assumption that all people will use the system primarily in the same way. Sure, there are some options built in — perhaps the same action can be initiated by either clicking on a button, selecting a menu item or invoking a keyboard short-cut. The problem is that when every variation needs to be coded into the system, the prospect of...

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        Topics: Business Intelligence, Data Management, natural language processing, data operations, Analytics and Data, AI and Machine Learning

        I recently described how the operational data platforms sector is in a state of flux. There are multiple trends at play, including the increasing need for hybrid and multicloud data platforms, the evolution of NoSQL database functionality and applicable use-cases, and the drivers for hybrid data processing. The past decade has seen significant change in the emergence of new vendors, data models and architectures as well as new deployment and consumption approaches. As organizations adopted...

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        Topics: business intelligence, Analytics, Data Integration, Data, AI and Machine Learning

        Organizations have been using data virtualization to collect and integrate data from various sources, and in different formats, to create a single source of truth without redundancy or overlap, thus improving and accelerating decision-making giving them a competitive advantage in the market. Our research shows that data virtualization is popular in the big data world. One-quarter (27%) of participants in our Data Lake Dynamic Insights Research reported they were currently using data...

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        Topics: embedded analytics, Analytics, Business Intelligence, Streaming Analytics, AI and Machine Learning

        I recently wrote about the importance of data pipelines and the role they play in transporting data between the stages of data processing and analytics. Healthy data pipelines are necessary to ensure data is integrated and processed in the sequence required to generate business intelligence. The concept of the data pipeline is nothing new of course, but it is becoming increasingly important as organizations adapt data management processes to be more data driven.

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        Topics: Analytics, Business Intelligence, Data Governance, Data Integration, Data, Digital Technology, Digital transformation, data lakes, data operations, Streaming Data Events, Analytics and Data, AI and Machine Learning

        I have written previously that the world of data and analytics will become more and more centered around real-time, streaming data. Data is created constantly and increasingly is being collected simultaneously. Technology advances now enable organizations to process and analyze information as it is being collected to respond in real time to opportunities and threats. Not all use cases require real-time analysis and response, but many do, including multiple use cases that can improve customer...

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        Topics: business intelligence, Analytics, Internet of Things, Data, Digital Technology, Streaming Analytics, Streaming Data Events, Analytics and Data, AI and Machine Learning

        For years, maybe decades, we have heard about the struggles between IT and line-of-business functions. In this perspective, we will look at some of the data from our Analytics and Data Benchmark Research about the roles of IT and line-of-business teams in analytics and data processes. We will also look at some of the disconnects between these two groups. And, by looking at how organizations are operating today and the results they are achieving, we can discern some of the best practices for...

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        Topics: Analytics, Business Intelligence, Data, Digital Technology, Analytics and Data, AI and Machine Learning

        Despite widespread and increasing use of the cloud for data and analytics workloads, it has become clear in recent years that, for most organizations, a proportion of data-processing workloads will remain on-premises in centralized data centers or distributed-edge processing infrastructure. As we recently noted, as compute and storage are distributed across a hybrid and multi-cloud architecture, so, too, is the data it stores and relies upon. This presents challenges for organizations to...

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        Topics: Analytics, Business Intelligence, Data Governance, Data, data operations, AI and Machine Learning

        The various NoSQL databases have become a staple of the data platforms landscape since the term entered the IT industry lexicon in 2009 to describe a new generation of non-relational databases. While NoSQL began as a ragtag collection of loosely affiliated, open-source database projects, several commercial NoSQL database providers are now established as credible alternatives to the various relational database providers, while all the major cloud providers and relational database giants now also...

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        Topics: Analytics, Data, AI and Machine Learning

        I recently described the emergence of hydroanalytic data platforms, outlining how the processes involved in generating energy from a lake or reservoir were analogous to those required to generate intelligence from a data lake. I explained how structured data processing and analytics acceleration capabilities are the equivalent of turbines, generators and transformers in a hydroelectric power station. While these capabilities are more typically associated with data warehousing, they are now...

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        Topics: Analytics, Data Governance, Data, Digital Technology, data lakes, data operations, Streaming Data Events, AI and Machine Learning

        The use of artificial intelligence (AI) using machine learning (ML) will be the single most important trend in business software this decade because it can multiply the investment value of such applications and provide vendors an important source of differentiation to achieve a competitive advantage in what are today very mature software categories. I assert that by 2025, almost all Office of Finance software vendors will have incorporated some AI capabilities to reduce workloads and improve...

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        Topics: Office of Finance, embedded analytics, Data Management, Business Planning, Financial Performance Management, ERP and Continuous Accounting, AI and Machine Learning

        As I stated when joining Ventana Research, the socioeconomic impacts of the pandemic and its aftereffects have highlighted more than ever the differences between organizations that can turn data into insights and are agile enough to act upon it and those that are incapable of seeing or responding to the need for change. Data-driven organizations stand to gain competitive advantage, responding faster to worker and customer demands for more innovative, data-rich applications and personalized...

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        Topics: Analytics, Business Intelligence, Data Integration, Data, data lakes, data operations, Streaming Data Events, AI and Machine Learning

        I recently described how the data platforms landscape will remain divided between analytic and operational workloads for the foreseeable future. Analytic data platforms are designed to store, manage, process and analyze data, enabling organizations to maximize data to operate with greater efficiency, while operational data platforms are designed to store, manage and process data to support worker-, customer- and partner-facing operational applications. At the same time, however, we see...

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        Topics: embedded analytics, Analytics, Business Intelligence, Data, Digital Technology, Streaming Data Events, Analytics and Data, AI and Machine Learning

        Organizations of all sizes are dealing with exponentially increasing data volume and data sources, which creates challenges such as siloed information, increased technical complexities across various systems and slow reporting of important business metrics. Migrating to the cloud does not solve the problems associated with performing analytics and business intelligence on data stored in disparate systems. Also, the computing power needed to process large volumes of data consists of clusters of...

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        Topics: Analytics, Business Intelligence, Data Integration, Data, data lakes, data operations, Streaming Analytics, AI and Machine Learning

        Ventana Research recently announced its 2022 Market Agenda for the Office of Finance, continuing the guidance we have offered since 2003 on the practical use of technology for the finance and accounting department. Our insights and best practices aim to enable organizations to operate with agility and resiliency, improving performance and delivering greater value as a strategic partner.

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        Topics: Office of Finance, Business Intelligence, Collaboration, Business Planning, Financial Performance Management, ERP and Continuous Accounting, Revenue, blockchain, robotic finance, Predictive Planning, AI and Machine Learning, lease and tax accounting

        Ventana Research recently announced its 2022 Market Agenda for the Office of Revenue, continuing the guidance we have offered for nearly two decades to help organizations realize optimal value from applying technology to improve business outcomes. Chief sales and revenue officers and their associated operations teams are experts in their respective fields but may not have the guidance needed to employ technology effectively. As we look to 2022, we are focusing on the entire selling and buying...

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        Topics: Sales, Analytics, Internet of Things, Data, Sales Performance Management, Digital Technology, Digital Commerce, Conversational Computing, mobile computing, Subscription Management, extended reality, intelligent sales, partner management, AI and Machine Learning

        Organizations today have huge volumes of data across various cloud and on-premises systems which keep growing by the second. To derive value from this data, organizations must query the data regularly and share insights with relevant teams and departments. Automating this process using natural language processing (NLP) and artificial intelligence and machine learning (AI/ML) enables line-of-business personnel to query the data faster, generate reports themselves without depending on IT, and...

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        Topics: embedded analytics, Analytics, Business Intelligence, Data Integration, Data, natural language processing, data lakes, data operations, AI and Machine Learning

        The internet is a rich source of information and is used by buyers to research new applications and offerings well before ever engaging a vendor and salesperson. Along with massive growth in offerings, this is a major reason why sales teams are facing increasing challenges to successfully sell and attain targets.

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        Topics: Sales, AI and Machine Learning

        Data lakes have enormous potential as a source of business intelligence. However, many early adopters of data lakes have found that simply storing large amounts of data in a data lake environment is not enough to generate business intelligence from that data. Similarly, lakes and reservoirs have enormous potential as sources of energy. However, simply storing large amounts of water in a lake is not enough to generate energy from that water. A hydroelectric power station is required to harness...

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        Topics: Analytics, Business Intelligence, Cloud Computing, Data Governance, Data Integration, Data, Digital Technology, data lakes, data operations, AI and Machine Learning

        As I noted when joining Ventana Research, the range of options faced by organizations in relation to data processing and analytics can be bewildering. When it comes to data platforms, however, there is one fundamental consideration that comes before all others: Is the workload primarily operational or analytic? Although most database products can be used for operational or analytic workloads, the market has been segmented between products targeting operational workloads, and those targeting...

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        Topics: business intelligence, Analytics, Data, data lakes, data operations, AI and Machine Learning

        With the emergence of multiple selling channels and the rise of the subscription model, the need for a unified approach to revenue planning and execution should be a priority for every organization. As I have written about in my analyst perspective Revenue Management: The Opportunity for Innovation and Optimization, this need to unify the approach and focus on alignment across all revenue supporting teams in furtherance of an organization’s objectives and targets is of key importance to ensure...

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        Topics: Sales, Customer Experience, Sales Performance Management, Subscription Management, AI and Machine Learning

        Any organization that relies heavily on a large labor force looks to automation to reduce costs, and contact centers are no exception. They handle interactions at such large scale that almost any effort to automate some part of the process can deliver measurable efficiencies. Two factors have ratcheted up attention on automating customer experience workflows: the dramatic expansion of digital interaction channels, and the development of artificial intelligence and machine learning tools to...

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        Topics: Customer Experience, Voice of the Customer, Analytics, Data Integration, Contact Center, Data, agent management, data operations, Experience Management, AI and Machine Learning

        TIBCO is a large, independent cloud-computing and data analytics software company that offers integration, analytics, business intelligence and events processing software. It enables organizations to analyze streaming data in real time and provides the capability to automate analytics processes. It offers more than 200 connectors, more than 200 enterprise cloud computing and application adapters, and more than 30 non-relational structured query language databases, relational database management...

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        Topics: embedded analytics, Analytics, Collaboration, Data Governance, Information Management, Data, Digital Technology, data lakes, AI and Machine Learning

        Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management. The platform enables personnel to work with relational databases, Apache Hadoop, Spark and NoSQL databases for cloud or on-premises jobs. Talend data integration software offers an open and scalable architecture and can be integrated with multiple data warehouses, systems and applications to provide a...

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        Topics: Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, Digital Technology, data lakes, AI and Machine Learning

        When migrating their communications stacks to the cloud, many organizations come face to face with a quandary: do they emphasize the business phone system and gravitate toward a unified communications vendor? Or should they focus on the specific applications needed for running their contact centers and seek out a CCaaS vendor?

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        Topics: Customer Experience, Voice of the Customer, Contact Center, agent management, AI and Machine Learning

        Enterprises looking to adopt cloud-based data processing and analytics face a disorienting array of data storage, data processing, data management and analytics offerings. Departmental autonomy, shadow IT, mergers and acquisitions, and strategic choices mean that most enterprises now have the need to manage data across multiple locations, while each of the major cloud providers and data and analytics vendors has a portfolio of offerings that may or may not be available in any given location. As...

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        Topics: Analytics, Cloud Computing, Data Governance, Data Integration, Data, Digital Technology, data lakes, data operations, AI and Machine Learning

        How does your organization define and display its metrics? I believe many organizations are not defining and displaying metrics in a way that benefits them most. If an organization goes through the trouble of measuring and reporting on a metric, the analysis ought to include all the information needed to evaluate that metric effectively. A number, by itself, does not provide any indication of whether the result is good or bad. Too often, the reader is expected to understand the difference, but...

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        Topics: Analytics, Business Intelligence, Internet of Things, Data, Digital Technology, Streaming Analytics, AI and Machine Learning

        When NICE acquired inContact in 2016, it began a transformation that saw it broaden its product offering and positioned itself to play a larger role in the contact center and customer experience industries. It was a prescient move, creating a firm that could supply end-to-end contact center functionality in the cloud. And it anticipated today’s market dynamic, in which NICE and its competitors are racing to define (and capitalize on) the post-contact center future.

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        Topics: Customer Experience, Voice of the Customer, Business Continuity, Analytics, Contact Center, Data, Digital transformation, agent management, Experience Management, AI and Machine Learning

        In part one of this Analyst Perspective on the use of artificial intelligence within contact center applications, we focused on the evolution — and resulting benefits — of tools embedded with AI, including ease-of-use for non-data-scientists.

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        Topics: Customer Experience, Voice of the Customer, Analytics, agent management, AI and Machine Learning

        Databricks is a data engineering and analytics cloud platform built on top of Apache Spark that processes and transforms huge volumes of data and offers data exploration capabilities through machine learning models. It can enable data engineers, data scientists, analysts and other workers to process big data and unify analytics through a single interface. The platform supports streaming data, SQL queries, graph processing and machine learning. It also offers a collaborative user interface —...

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Information Management, Data, data lakes, AI and Machine Learning

        The work environment today demands that your organization advances the efficiency to execute business processes for continuous operations to have a positive impact on business performance. The capability to be responsive to any range of minor to disruptive business events is required to support business continuity and level of organizational readiness to meet the needs of digital business. Ventana Research asserts that in 2025, one-quarter of organizations will remain digitally ineffective in...

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        Topics: Customer Experience, Voice of the Customer, embedded analytics, Analytics, Business Intelligence, Cloud Computing, Contact Center, Data, Digital Technology, Operations & Supply Chain, Enterprise Resource Planning, Digital transformation, natural language processing, continuous supply chain, agent management, Process Mining, Streaming Analytics, Experience Management, AI and Machine Learning

        When artificial intelligence emerged from the labs and vendors started offering it as a component of their software, many contact-center buyers shied away from it. From their point of view, AI and machine learning tools were new, expensive, relatively untested and had an uncertain use case. This stance was understandable, as contact center professionals are traditionally expected to be risk-averse when deploying technology into their operations. Contact centers are, by design, supposed to be...

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        Topics: Customer Experience, Voice of the Customer, Analytics, Contact Center, agent management, AI and Machine Learning

        Access to external data can provide a competitive advantage. Our research shows that more than three-quarters (77%) of participants consider external data to be an important part of their machine learning (ML) efforts. The most important external data source identified is social media, followed by demographic data from data brokers. Organizations also identified government data, market data, environmental data and location data as important external data sources. External data is not just part...

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        Topics: Analytics, Business Intelligence, Internet of Things, Data, Digital Technology, Lease Management, Streaming Data, Streaming Analytics, AI and Machine Learning

        Alteryx is a data analytics software company that offers data preparation and analytics tools to simplify and automate data wrangling, data cleaning and modeling processes, enabling line-of-business personnel to quickly access, manipulate, analyze and output data. The platform features tools to run a variety of analytic functions such as diagnostic, predictive, prescriptive and geospatial analytics in a unified platform, and can connect to various data warehouses, cloud applications,...

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Preparation, Data, AI and Machine Learning

        Collibra is a data governance software company that offers tools for metadata management and data cataloging. The software enables organizations to find data quickly, identify its source and assure its integrity. Line-of-business workers can use it to create, review and update the organization's policies on different data assets. Collibra’s software uses a microservice architecture and open application programming interfaces to connect to various data ecosystems. Its data intelligence cloud...

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        Topics: Analytics, Business Intelligence, Data Governance, Data Preparation, Information Management, Data, data lakes, AI and Machine Learning

        Sisu Data is an analytics platform for structured data that uses machine learning and statistical analysis to automatically monitor changes in data sets and surface explanations. It can prioritize facts based on their impact and provide a detailed, interpretable context to refine and support conclusions. The product features fact boards, annotations and the ability to share facts and analysis across teams. Data teams and analysts start by creating common definitions of key performance...

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data, AI and Machine Learning

        Subscription management and billing services help organizations offer unique benefits and enhance delivery to customers. By making services more personalized, organizations can acquire – and retain – more customers.

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        Topics: Sales, Office of Finance, Continuous Planning, embedded analytics, Analytics, Business Intelligence, Business Planning, Product Information Management, Digital Commerce, Operations & Supply Chain, Enterprise Resource Planning, ERP and Continuous Accounting, natural language processing, revenue and lease accounting, continuous supply chain, Subscription Management, partner management, Process Mining, Streaming Analytics, Supplier Relationship Management, AI and Machine Learning

        Customer support operations increasingly rely on automation and complex workflow processes to reduce costs and improve experiences. Automation also allows organizations to make their service processes richer, incorporating information and staff from back offices, for example, or embedding conversational tools into contact center processes.

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        Topics: Customer Experience, embedded analytics, Analytics, Contact Center, natural language processing, agent management, Process Mining, Streaming Analytics, AI and Machine Learning

        Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization. Rapidminer Studio is its visual workflow designer for the creation of predictive models. It offers more than 1,500 algorithms and functions in their library, along with templates, for...

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Preparation, Data, data lakes, AI and Machine Learning

        Confluent Platform is a streaming platform built by the original creators of Apache Kafka. It enables organizations to organize and manage streaming data from various sources. Confluent launched its IPO in June this year and raised $828 million to further expand its business. Confluent Platform was brought to several public cloud vendor marketplaces last year as Confluent Cloud. The offering is currently available in Azure, AWS, and GCP marketplaces. Furthermore, the company strengthened its...

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data, AI and Machine Learning

        The annual Ventana Research Digital Innovation Awards showcase advances in the productivity and potential of business applications, as well as technology that contributes significantly to the improved processes and performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations to advance business and IT.

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        Topics: Customer Experience, Analytics, Internet of Things, Digital Technology, blockchain, natural language processing, Awards, Conversational Computing, collaborative computing, mobile computing, extended reality, AI and Machine Learning

        The annual Ventana Research Digital Innovation Awards showcase advances in the productivity and potential of business applications, as well as technology that contributes significantly to the improved processes and performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations to advance business and IT.

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        Topics: Continuous Planning, Analytics, Product Information Management, Price and Revenue Management, Digital Technology, Operations & Supply Chain, Enterprise Resource Planning, Conversational Computing, collaborative computing, continuous supply chain, work experience management, AI and Machine Learning

        The annual Ventana Research Digital Innovation Awards showcase advances in the productivity and potential of business applications, as well as technology that contributes significantly to the improved processes and performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations to advance business and IT.

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        Topics: Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, Digital Technology, blockchain, data lakes, AI and Machine Learning

        Dialpad provides contact center and business phone services, a market that is in transition due to a convergence of technologies and business conditions.

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        Topics: Customer Experience, Voice of the Customer, Analytics, Collaboration, Contact Center, natural language processing, agent management, AI and Machine Learning

        The annual Ventana Research Digital Innovation Awards showcase advances in the productivity and potential of business applications, as well as technology that contributes significantly to the improved processes and performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations to advance business and IT.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Internet of Things, Digital Technology, natural language processing, AI and Machine Learning

        The annual Ventana Research Digital Innovation Awards showcase advances in the productivity and potential of business applications, as well as technology that contributes significantly to the improved processes and performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations to advance business and IT.

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        Topics: Sales, Analytics, Product Information Management, Digital Commerce, AI and Machine Learning

        A year of business uncertainty, lockdowns and operational disruptions forced finance and accounting organizations to adapt and change in many ways that are proving to be permanent. The need to operate virtually resulted in some organizations accelerating their adoption of technology, bringing them closer to achieving a transformation of the finance and accounting function: reshaping the department into an organization that is more forward-looking and strategic. Strategic in the sense of...

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        Topics: Office of Finance, Business Intelligence, Data Governance, Data Preparation, Business Planning, Financial Performance Management, ERP and Continuous Accounting, blockchain, robotic finance, Predictive Planning, AI and Machine Learning

        The annual Ventana Research Digital Innovation Awards showcase advances in the productivity and potential of business applications, as well as technology that contributes significantly to the improved processes and performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations to advance business and IT.

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        Topics: Customer Experience, Human Capital Management, Marketing, Office of Finance, Voice of the Customer, Continuous Planning, embedded analytics, Learning Management, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Internet of Things, Business Planning, Contact Center, Data, Product Information Management, Sales Performance Management, Workforce Management, Financial Performance Management, Price and Revenue Management, Digital Technology, Digital Marketing, Digital Commerce, Operations & Supply Chain, Enterprise Resource Planning, ERP and Continuous Accounting, Revenue, blockchain, natural language processing, data lakes, Total Compensation Management, robotic finance, Predictive Planning, employee experience, candidate engagement, Conversational Computing, Continuous Payroll, collaborative computing, mobile computing, continuous supply chain, Subscription Management, agent management, extended reality, intelligent marketing, sales enablement, work experience management, robotic automation, AI and Machine Learning, lease and tax accounting

        As mentioned in my Analyst Perspective, Revenue Performance Management: Leadership and Operations for Optimal Outcomes, there is continuing pressure on sales leaders to deliver against sales targets in increasingly competitive markets. Among the various levers that sales leadership can use to support these efforts, are applications and processes that best position sales teams to achieve targets, such as planning and allocating territories, establishing quotas and devising incentive compensation...

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        Topics: Sales, Analytics, Sales Performance Management, Price and Revenue Management, sales enablement, AI and Machine Learning

        Customer Service & Support (CSS) is a software segment that provides tools for tracking and resolving customer problems, primarily through contact centers. The segment has been mature for decades but today is reinvigorated by a new emphasis on workflows and automation. Vendors, like ServiceNow, have been innovative in developing new technologies for managing self-service and field service, and providing agents with contextually relevant information during interactions. The new technologies...

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        Topics: Customer Experience, Voice of the Customer, Analytics, Contact Center, Product Information Management, Digital Commerce, Subscription Management, agent management, AI and Machine Learning

        We are happy to share some insights about Amazon QuickSight drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about Google Looker drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about ThoughtSpot drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about TIBCO Spotfire drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, AI and Machine Learning

        We are happy to share some insights about Sisense drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about Infor Birst drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Preparation, Data, Information Management (IM), natural language processing, AI and Machine Learning

        We are happy to share some insights about Microsoft Power BI drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about Tableau drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about SAS drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        Teradata introduced some enhancements to its Vantage platform last year in which they expanded its analytics functions and language support, and strengthened tools to improve collaboration between data scientists, business analysts, data engineers and business personnel. Some of the key enhancements included expanding the native support for R and Python, extending the ability to execute a wide range of open-source analytics algorithms, and automatic generation of SQL from R and Python code....

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Preparation, Information Management, Data, AI and Machine Learning

        We are happy to share some insights about SAP drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Data, natural language processing, AI and Machine Learning

        There has been a lot of market activity around vendors offering sales-forecasting products (or functionality to address sales forecasting) as part of a wider technology offering for sales and revenue management. As I have discussed in my Analyst Perspective: The Art and Science of Sales from the Inside Out, the pandemic accelerated the prior trends that are now forcing sales leaders and sales teams to reexamine traditional notions of how B2B sales are conducted. In addition, with the rise of...

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        Topics: Sales, Office of Finance, Analytics, Business Planning, Sales Performance Management, Price and Revenue Management, AI and Machine Learning

        We are happy to share some insights about Board International drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about Yellowfin drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        As laid out in my recent Analyst Perspective, Revenue Management: The Opportunity for Innovation and Optimization, revenue management is a new way look at generating and managing the top line. It unifies multiple sources: the traditional focus on new customers to existing customers as well as all types of revenue from new, additional channels. This could include customer retention, upsell and cross sell, in addition to other selling channels such as through partners or digital sales channels...

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        Topics: Sales, Analytics, Sales Performance Management (SPM), Price and Revenue Management, Digital Commerce, Subscription Management, AI and Machine Learning

        We are happy to share some insights about Domo drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about Oracle Analytics Cloud drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, AI and Machine Learning

        We are happy to share some insights about Qlik drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Data, Information Management (IM), natural language processing, AI and Machine Learning

        We are happy to share some insights about Information Builders’ WebFOCUS Business Intelligence and Analytics Platform drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about MicroStrategy drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        We are happy to share some insights about IBM drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Information Management, natural language processing, AI and Machine Learning

        Customer service and support (CSS) is a term with two meanings. Most generally, it refers to the functions of a contact center in handling post-sales customer inquiries that require some effort or action on the part of the business. More specifically, it refers to the elements of the software stack that facilitate those operations, primarily case tracking and trouble ticketing.

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        Topics: Customer Experience, Analytics, Contact Center, agent management, AI and Machine Learning

        Alation recently announced the release of its 2021.1 version, introducing new data governance capabilities, enhancements in search and discovery through data domains, and extended connector and query coverage for data sources. Alation’s new federated authentication enables users to query cloud services such as Amazon Web Services, Snowflake, Tableau and more, using a single sign-on. The release also includes a Search application programming interface that allows for the integration of Alation...

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        Topics: Analytics, Business Intelligence, Collaboration, Data Preparation, Data, Information Management (IM), AI and Machine Learning

        Unit4’s Financial Planning and Analysis (formerly Prevero) is a planning and budgeting application designed for the requirements of midsize corporations and the public sector. These organizations are challenged in buying software because they have almost all the requirements of larger enterprises but have a smaller budget and limited technical resources.

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        Topics: Office of Finance, embedded analytics, Analytics, Business Intelligence, Business Planning, Financial Performance Management, Price and Revenue Management, Digital Technology, ERP and Continuous Accounting, Predictive Planning, collaborative computing, AI and Machine Learning

        Observed both here and elsewhere, average sales quota attainments appear to be in an exorable decline. As I discussed in my recent Analyst Perspective, "The Art and Science of Sales from the 'Inside Out'," vendors of sales technology have reacted to this by adding a slew of new functionality including the potential for artificial intelligence (AI) to be a game changer for sales. One can argue that this use of AI is still relatively immature having been generally available only since 2014, but...

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        Topics: Sales, Human Capital Management, Analytics, Business Intelligence, Sales Performance Management, candidate engagement, sales enablement, AI and Machine Learning

        Machine learning is valuable for organizations, but it can be hard to deploy. Our Machine Learning Dynamic Insights research identifies that not having enough skilled resources and difficulty building and maintaining ML systems are pressing challenges organizations face in applying ML. Traditional ML model development is resource-intensive, requiring significant domain knowledge and time to produce and compare dozens of models. And as the number of ML models grow, their management becomes...

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Data, AI and Machine Learning

        As I have discussed in my Analyst Perspective, The Art of Sales, from the Inside Out, the challenges facing direct sales leaders are not going away. Declining quota attainment, lack of visibility into deal health and difficulty in forecasting quarterly sales remain a challenge for sales leaders, resulting in a continuing reduction in duration of tenure.

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        Topics: Sales, Analytics, Sales Performance Management, Price and Revenue Management, sales enablement, AI and Machine Learning

        Voice of the Customer (VoC) is a catch-all term that refers to the collection of customer feedback in various formats. Sometimes this feedback is in the form of quick surveys or reactions to questions like, "Did I resolve your issue today?" or "Would you recommend our service to a friend?" Alternatively, it can be derived from less specific but more numerous data signals that span multiple interactions or across a customer base. Most businesses make an effort to capture some customer feedback.

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        Topics: Customer Experience, Voice of the Customer, Analytics, Contact Center, agent management, AI and Machine Learning

        Organizations are becoming more and more data-driven and are looking for ways to accelerate the usage of artificial intelligence and machine learning (AI/ML). Developing and deploying AI/ML models can be complicated in many ways, often involving different tools and services to manage these solutions from end to end. Accessing and preparing data is the most common challenge organizations face in this process, and consequently, AI/ML vendors typically incorporate tools to address this part of the...

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        Topics: business intelligence, Analytics, Collaboration, Data Governance, Data Preparation, Data, AI and Machine Learning

        IBM Planning Analytics, formerly known as TM1, is a comprehensive planning and analytics application designed to integrate and streamline an organization’s planning processes. It can support multiple planning use cases on a single platform, including financial, headcount, sales and demand planning. The software automates enterprise-wide data collection to make it repeatable and scalable across multiple users and departments. It supports sophisticated driver-based modeling that enables rapid...

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        Topics: Office of Finance, embedded analytics, Analytics, Business Intelligence, Collaboration, Business Planning, ERP and Continuous Accounting, Predictive Planning, AI and Machine Learning

        Process-mining software isn’t exactly new, but it’s also not widely known in the software technology market. The discipline has been around for at least a decade, but is generating more interest these days with both specialist vendors and major enterprise software vendors offering process-mining products and services. We assert that through 2022, 1 in 4 organizations will look to streamline their operations by exploring process mining.

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        Topics: business intelligence, Analytics, Digital Technology, AI and Machine Learning

        Digital commerce affects almost everyone’s lives. It is hard to remember a time when one could not sign on to a website like Amazon, order a product, pay for it and have it delivered to your front door within days, not weeks. Although catalogues have been around for a century or so, the digital-commerce revolution has changed the way we think about shopping for many of our everyday and special occasion products. Extend this to digital services, such as streaming videos or online games, and...

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        Topics: Sales, Customer Experience, Analytics, Business Intelligence, Product Information Management, Price and Revenue Management, Digital Commerce, AI and Machine Learning

        Organizations are accelerating their digital transformation and looking for innovative ways to engage with customers in this new digital era of data management. The goal is to understand how to manage the growing volume of data in real time, across all sources and platforms, and use it to inform, streamline and transform internal operations. Over the years, the adoption of cloud computing has gained momentum with more and more organizations trying to make use of applications, data, analytics...

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Information Management, Internet of Things, Data, natural language processing, AI and Machine Learning

        Having just completed the 2021 Ventana Research Value Index for Analytics and Data, I want to share some of my observations about how the market has advanced since our assessment two years ago. The analytics software market is quite mature and products from any of the vendors we assess can be used to effectively deliver information to help your organization improve its operations. However, it’s also interesting to see how much the market continues to advance and how much investment vendors...

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        Topics: Big Data, Key Performance Indictors, embedded analytics, exadata, Analytics, Business Collaboration, Business Intelligence, Collaboration, Data Preparation, Digital Technology, natural language processing, Conversational Computing, collaborative computing, mobile computing, AI and Machine Learning

        The pandemic accelerated several trends in the contact-center industry that were already underway, chiefly: moving infrastructure and software applications to the cloud, and rethinking the process of managing agents. One byproduct of these trends is a renewed look at the similarities between business-phone systems (also known as unified communications, or UC) and contact center systems (CC).

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        Topics: Customer Experience, Analytics, Collaboration, Contact Center, agent management, AI and Machine Learning

        There is no doubt that the pandemic has accelerated the existing need for new technology that can help sales professionals do their jobs well in this quickly evolving market. In addition, market trends are driving the need for functionality that is aimed at the front-line sales professional and the manager, highlighting the demand for tools that can help arrest the decline in quota attainment, as well as helping salespeople supplement their traditional focus on sales quotas with activities such...

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        Topics: Sales, embedded analytics, Analytics, Internet of Things, Sales Performance Management, natural language processing, sales enablement, AI and Machine Learning

        Organizations are increasingly using data as a strategic asset, which makes data services critical. Huge volumes of data need to be stored, managed, discovered and analyzed. Cloud computing and storage approaches provide enterprises with various capabilities to store and process their data in third-party data centers. The advent of data platforms previously discussed here are essential for organizations to effectively manage their data assets.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Lake, Data Preparation, Data, AI and Machine Learning, Microsoft Azure

        The current pandemic has disrupted many of the traditional sales methods used by field-sales organizations to engage, and sell to, buyers. In an effort to provide help, many vendors have recently announced new features that focus less on the management of sales organizations and more on tools to help salespeople sell. This has been coupled with a renewed interest in using data to help with the science, alongside the art, of selling, as referenced in my AP: The Art and Science of Sales from the...

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        Topics: Sales, Analytics, Data, Product Information Management, Sales Performance Management (SPM), Digital Technology, sales enablement, AI and Machine Learning

        Ventana Research recently announced its 2021 market agenda for the Office of Finance, continuing the guidance we’ve offered since 2003 on the practical use of technology for the finance and accounting department. Our insights and best practices aim to enable organizations to operate with agility and resiliency, improving performance and delivering greater value as a strategic partner.

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        Topics: Office of Finance, enterprise profitability management, Business Intelligence, Collaboration, Business Planning, Financial Performance Management, ERP and Continuous Accounting, Revenue, blockchain, robotic finance, Predictive Planning, virtual audit, AI and Machine Learning, virtual close, lease and tax accounting

        Ventana Research recently announced its 2021 research agenda for the Office of Sales, continuing the guidance we’ve offered for nearly two decades to help organizations realize optimal value from applying technology to improve business outcomes. Chief sales and revenue officers are experts in their respective fields but may not have the guidance needed to employ technology effectively. As we look to 2021, we are focusing on the entire selling and buying journey and the applications that...

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        Topics: Sales, Analytics, Financial Performance, Internet of Things, Data, Sales Performance Management, Digital Technology, Digital Commerce, mobile computing, Subscription Management, extended reality, intelligent sales, partner management, Machine Conversational Computing, Office of Revenue, AI and Machine Learning

        I’m proud to share Ventana Research’s 2021 market agenda for digital technology. Our focus in this agenda is to deliver expertise to help organizations prioritize technology investments that increase workforce effectiveness and organizational agility, ensuring ongoing operation during any type of disruption.

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        Topics: Big Data, Analytics, Cloud Computing, Internet of Things, Digital Technology, Robotic Process Automation, blockchain, Conversational Computing, mobile computing, extended reality, AI and Machine Learning

        Ventana Research recently announced its 2021 market agenda in the expertise area of Customer Experience. Most organizations have some degree of focus on managing how they interact with their customers, but it is often a disjointed and constrained process. Developing an effective customer experience has become an investment priority in recent years as organizations increasingly recognize the importance of good experiences to profitability, customer longevity and advocacy on behalf of brands.

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        Topics: Sales, Customer Experience, Marketing, Voice of the Customer, Analytics, Customer Service, Contact Center, Workforce Management, Digital Marketing, Digital Commerce, agent management, AI and Machine Learning

        Ventana Research recently announced its 2021 market agenda for Analytics, continuing the guidance we’ve offered for nearly two decades to help organizations derive optimal value from technology investments to improve business outcomes.

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        Topics: embedded analytics, Analytics, Business Intelligence, natural language processing, Process Mining, Streaming Analytics, AI and Machine Learning

        The industry is making huge strides with artificial intelligence (AI) and machine learning (ML). There is more data available to analyze. Analytics vendors have made it easier to build and deploy models, and AI/ML is being embedded into many types of applications. Organizations are realizing the value that AI/ML provides and there are now millions of professionals with AI or ML in their title or job description. AI/ML is even being used to make many aspects of itself easier. Organizations that...

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        Topics: Sales, Customer Experience, Marketing, Analytics, Business Intelligence, Data Preparation, Digital Technology, AI and Machine Learning

        BlackLine recently held its first virtual user conference, Beyond the Black, where it detailed numerous additions and enhancements to its applications. Of note was the launch of BlackLine Cash Application, an accounts receivable (AR) processing software based on software originally developed by recently acquired Rimilia. The new application fits the company's product strategy of providing accounting departments with software that automates time-consuming repetitive tasks and substantially...

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        Topics: Office of Finance, Business Planning, Financial Performance Management, ERP and Continuous Accounting, AI and Machine Learning

        In the context of planning, budgeting and benchmarking, external data includes information about the world outside an organization such as economic and market statistics, competitors and customers. Today, a comprehensive set of external data is a “nice to have” item in most organizations, but that’s likely to change. External data is necessary for useful and accurate business-focused planning and budgeting, and for performance benchmarking. It is also essential for the effective applications of...

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        Topics: Information Management, Business Planning, Financial Performance Management, Predictive Planning, AI and Machine Learning

        Organizations are dealing with exponentially increasing data that ranges broadly from customer-generated information, financial transactions, edge-generated data and even operational IT server logs. A combination of complex data lake and data warehouse capabilities are required to leverage this data. Our research shows that nearly three-quarters of organizations deploy both data lakes and data warehouses but are using a variety of approaches which can be cumbersome. A single platform that can...

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        Topics: PROS Pricing, embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Data, data lakes, AI and Machine Learning

        Businesses are transforming their organizations, building a data culture and deploying sophisticated analytics more broadly than ever. However, the process of using data and analytics is not always easy. The necessary tools are often separate, but our research shows organizations prefer an integrated environment. In our Data Preparation Benchmark Research, we found that 41% of participants use Analytics and Business Intelligence tools for data preparation.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Preparation, Information Management, Internet of Things, Data, Digital Technology, natural language processing, Conversational Computing, AI and Machine Learning

        Traditional on-premises data processing solutions have led to a hugely complex and expensive set of data silos where IT spends more time managing the infrastructure than extracting value from the data. Big data architectures have attempted to solve the problem with large pools of cost-effective storage, but in doing so have often created on-premises management and administration challenges. These challenges of acquiring, installing and maintaining large clusters of computing resources gave rise...

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Data, data lakes, AI and Machine Learning

        Organizations are always looking to improve their ability to use data and AI to gain meaningful and actionable insights into their operations, services and customer needs. But unlocking value from data requires multiple analytics workloads, data science tools and machine learning algorithms to run against the same diverse data sets. Organizations still struggle with limited data visibility and insufficient insights, which are often caused by a multitude of reasons such as analytic workloads...

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Data, Information Management (IM), data lakes, AI and Machine Learning

        The pandemic has raised the stakes for self-service in every part of the customer journey. In 2020, the customer service industry underwent a shock to its collective system by pulling up stakes and moving agents to remote work. At the same time, consumers moved away from in-person interactions in stores and branches. This systemic disruption has led to longer call wait times and tougher interactions because collaborating and accessing company data systems from outside the office is difficult.

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        Topics: Customer Experience, Contact Center, Digital Technology, natural language processing, Conversational Computing, agent management, AI and Machine Learning

        Can you imagine a more arcane and boring topic than accounts receivable? Unless you are the CFO, controller, chief accounting officer or treasurer of an organization, maybe not. Anecdotally, as it’s part of the trend to the digital transformation of all things in the department, there appears to be greater interest in this area of the Office of Finance. With populations locked down and the accounting staff unable to work in an office, the need to operate virtually has accelerated the...

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        Topics: Office of Finance, Financial Performance Management, ERP and Continuous Accounting, robotic finance, AI and Machine Learning

        Teradata is not a name that is commonly associated with the customer experience marketplace, but that is likely to change as customer experience (CX) practitioners wrestle with the problems created by the multiple streams of data thrown off by the many applications and customer touchpoints they have to manage. Teradata’s Vantage CX is a tool for ingesting and managing customer information at great scale, combining the functions of a modern CDP with the analytics that makes customer data...

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        Topics: Customer Experience, Marketing, Analytics, Business Intelligence, Contact Center, Data, Digital Marketing, Digital Commerce, intelligent marketing, AI and Machine Learning

        Although historically there has been a hard divide between what are colloquially called “Inside and Field Sales,” changes over the last 10 years have narrowed the distinction. The pandemic has only accelerated the path to unifying sales activities commonly performed to engage buyers and customers. Characterized by a very disciplined and controlled endeavor, inside sales teams have been heavier users of technology. This has enabled more productive engagement including emails and calls, as well...

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        Topics: Sales, embedded analytics, Analytics, Business Intelligence, Collaboration, Internet of Things, Sales Performance Management (SPM), natural language processing, intelligent sales, sales enablement, AI and Machine Learning

        The annual Ventana Research Digital Innovation Awards showcases advances in the productivity and potential of business applications, as well as technology that contributes significantly to improved efficiency and productivity in the processes and the performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations that advance business and IT.

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        Topics: Analytics, Collaboration, Data Governance, Data Lake, Data Preparation, IOT, Data, Information Management (IM), Digital Technology, blockchain, Conversational Computing, collaborative computing, mobile computing, extended reality, AI and Machine Learning

        Determining and providing the appropriate compensation for each person — whether it involves base pay, variable pay such as commissions or bonuses or longer-term incentives in the form of cash or equity or other rewards — is critical to being able to attract and retain productive members of the workforce, whether full- or part-time employees, contingent workers or contractors. The complexities of compensation often prove to be a core challenge for human resources departments as they strive to...

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        Topics: Analytics, collaborative computing, total rewards management, AI and Machine Learning

        Enterprise resource planning (ERP) systems are central to nearly every organization’s management of operational and financial business processes. They are essential to the smooth functioning of an organization’s record keeping, accounting and finance tasks. In manufacturing and distribution, ERP manages inventory and logistics. Some ERP software vendors incorporate an extended set of capabilities that include managing human resources as well as supply chains and logistics. In the 2020s,...

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        Topics: Office of Finance, Financial Performance Management, ERP and Continuous Accounting, robotic finance, Predictive Planning, AI and Machine Learning

        The annual Ventana Research Digital Innovation Awards showcases advances in the productivity and potential of business applications, as well as technology that contributes significantly to improved efficiency and productivity in the processes and the performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations that advance business and IT.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Digital Technology, natural language processing, Conversational Computing, collaborative computing, mobile computing, AI and Machine Learning

        This has been a dramatic year for contact centers. The underlying technology has been changing for some time, but that change is now accelerating because of the urgent operational shifts forced by the pandemic. When you can’t gather dozens or hundreds of people into a single, open-plan site, you must look at alternative models for staffing and interaction handling. You must also work harder to create positive customer experiences across multiple contact channels.

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        Topics: Customer Experience, Voice of the Customer, Analytics, Contact Center, Product Information Management, Digital Commerce, Subscription Management, agent management, AI and Machine Learning

        The annual Ventana Research Digital Innovation Awards showcases advances in the productivity and potential of business applications, as well as technology that contributes significantly to improved efficiency and productivity in the processes and the performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations that advance business and IT.

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        Topics: Sales, Marketing, embedded analytics, Analytics, Sales Performance Management, Digital Technology, intelligent marketing, sales enablement, AI and Machine Learning

        The annual Ventana Research Digital Innovation Awards showcases advances in the productivity and potential of business applications, as well as technology that contributes significantly to improved efficiency and productivity in the processes and performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations that advance business and IT.

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        Topics: Customer Experience, Human Capital Management, Marketing, Analytics, Internet of Things, Contact Center, Data, Digital Technology, Digital Commerce, Operations & Supply Chain, blockchain, employee experience, candidate engagement, Conversational Computing, collaborative computing, mobile computing, agent management, extended reality, business digital commerce, work experience management, AI and Machine Learning

        Ventana Research has been evaluating analytics and business intelligence (BI) software for a long time—almost 20 years. Our methodology for these assessments is referred to as a Value Index. We use weightings derived from our benchmark research about how you, as buyers of these technologies, value and evaluate vendors. You can view our 2019 Value Index results here. I am in the process of completing the 2020 evaluation now.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, natural language processing, Conversational Computing, collaborative computing, AI and Machine Learning

        The last decade has seen exponential growth amongst subscription-based business models. Pioneered in the B2C market with cloud-based SaaS offerings, the last decade has seen exponential growth in the share of the economy that is now subscription based. Increasingly, this modern business model is permeating throughout more traditional style industries and companies. But regardless of whether a company is natively subscription based, or is transitioning, maintaining this growth requires...

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        Topics: Sales, Customer Experience, Office of Finance, Voice of the Customer, embedded analytics, Analytics, Business Intelligence, Collaboration, Internet of Things, Contact Center, Product Information Management, Price and Revenue Management, Digital Commerce, Enterprise Resource Planning, ERP and Continuous Accounting, natural language processing, robotic finance, revenue and lease accounting, Subscription Management, agent management, intelligent sales, sales enablement, AI and Machine Learning

        An important recent development in software designed for the Office of Finance is the addition of what we’re calling a data aggregation device (DAD) for analytical applications. A DAD automates the collection of data from disparate sources using, for example, application programming interfaces (APIs) and robotic process automation (RPA). With a DAD, users of the analytical application have immediate access to a much broader data set; one that incorporates operational as well as financial data...

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        Topics: Office of Finance, Analytics, Business Intelligence, Data, Financial Performance Management, Price and Revenue Management, robotic finance, Predictive Planning, AI and Machine Learning

        Subscription-based business models have seen exponential growth over the last decade. The growth of this recurring revenue business model, where a subscriber commits to repeatedly pay for a good or device for a fixed or indefinite timeline, has been caused by the shift from the one-time selling of physical products to selling digital services on a subscription basis. The first phase of this transformation was led by “digitally native” organizations, typically B2C, that have only ever offered...

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        Topics: Sales, Customer Experience, Office of Finance, Voice of the Customer, embedded analytics, Analytics, Business Intelligence, Collaboration, Internet of Things, Contact Center, Product Information Management, Price and Revenue Management, Digital Commerce, Enterprise Resource Planning, ERP and Continuous Accounting, natural language processing, robotic finance, revenue and lease accounting, Subscription Management, agent management, intelligent sales, sales enablement, AI and Machine Learning

        I’m very excited to announce to my network as well as the ever-expanding Ventana Research community that I’m now directing Ventana Research’s Office of Sales practice. The focus is to guide and educate sales and business professionals on the selling applications and technology including digital commerce, price and revenue management, product information management, sales enablement, sales performance management and subscription management. While these are the main topics of our Office of Sales...

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        Topics: Sales, embedded analytics, Analytics, Business Intelligence, Collaboration, Data, Product Information Management, Sales Performance Management, Price and Revenue Management, Digital Technology, Work and Resource Management, Conversational Computing, collaborative computing, mobile computing, intelligent sales, sales enablement, AI and Machine Learning

        One of the challenges of being a practically minded technology analyst is squaring the importance of “the next big thing” with the reality of what most organizations are doing. For decades it’s been the case that “the next big thing” in the world of information technology is easily several years ahead of where most organizations are in their use of technology. And before most organizations can realize the benefit of some whiz-bang technology, they frequently need to address a range of more...

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        Topics: Human Capital Management, Marketing, Office of Finance, Analytics, Business Intelligence, Sales Performance Management, Financial Performance Management, Price and Revenue Management, Digital Marketing, Work and Resource Management, Digital Commerce, Operations & Supply Chain, Enterprise Resource Planning, ERP and Continuous Accounting, robotic finance, Predictive Planning, revenue and lease accounting, Subscription Management, intelligent sales, AI and Machine Learning

        The workforce is an essential part of an organization’s overall business potential because it ensures continuous operations, even in black-swan events. The workforce is the core of the organization and should get the attention it deserves. In challenging times, a “customer-first” mentality tends to take hold — this is not unreasonable but in focusing on satisfying customers and opportunities, business leaders too often forget that the workforce experience is essential to achieving desired...

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        Topics: Sales, Customer Experience, Human Capital Management, Office of Finance, Voice of the Customer, Continuous Planning, Business Continuity, Analytics, Business Planning, Workforce Analytics, Workforce Management, Digital Technology, Operations & Supply Chain, Robotic Process Automation, employee experience, Conversational Computing, collaborative computing, mobile computing, agent management, People Analytics, AI and Machine Learning

        Analytics and data provide visibility into an organization’s past, present and potential performance. However, not all organizations are using analytics that provide timely insights — insights that not just reflect what happen but direct a successful course for the future. Demand for personalized and relevant insight only intensifies in a black-swan event. To maintain business continuity in times of pressure, it is critical that organizations not waste any time or resources when using analytics...

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        Topics: business intelligence, embedded analytics, Analytics, Business Intelligence, Collaboration, Internet of Things, Data, Digital Technology, natural language processing, Conversational Computing, AI and Machine Learning

        The workforce is the center of any organization, no matter if the workforce consists of employees, contractors or what we call gig workers. It stands to reason that a black-swan event has an immediate impact on a workforce and thus an organization’s overall business health. In challenging times, a “family-first” mentality tends to take hold — a reality that, far too often, business leaders and HR organizations underestimate. But organizational readiness is essential for sustainability and...

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        Topics: Sales, Human Capital Management, Learning, Office of Finance, Voice of the Customer, Analytics, Digital Technology, Digital Marketing, Operations & Supply Chain, Workforce Optimization, AI and Machine Learning

        Artificial intelligence (AI) and machine learning (ML) are all the rage right now. Our Machine Learning Dynamic Insights research shows that organizations are using these techniques to achieve a competitive advantage and improve both customer experiences and their bottom line. One type of analysis an organization can perform using AI and ML is predictive analytics. Organizations also need to plan their operations to predict the amount of cash they will need, inventory levels and staffing...

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        Topics: Office of Finance, Analytics, Business Intelligence, Financial Performance Management, Digital Technology, Predictive Planning, AI and Machine Learning

        I was recently asked to identify key modern data architecture trends. Data architectures have changed significantly to accommodate larger volumes of data as well as new types of data such as streaming and unstructured data. Here are some of the trends I see continuing to impact data architectures.

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        Topics: Analytics, Business Intelligence, Data Governance, Data Preparation, Data, Information Management (IM), Digital Technology, data lakes, AI and Machine Learning

        Ventana Research recently announced its 2020 research agenda for analytics, continuing the guidance we’ve offered for nearly two decades to help organizations derive optimal value from their technology investments and improve business outcomes.

        It’s been exciting to follow the emergence of innovative capabilities in the analytics market, but for businesses it can be challenging to stay on top of all these changes. To help, we craft our research agenda using our firm’s knowledge of technology...

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Internet of Things, natural language processing, AI and Machine Learning

        Ventana Research recently announced its 2020 research agenda for digital technology, continuing the guidance we’ve offered for nearly two decades to help organizations derive optimal value and improve business outcomes. While we have seen more than four decades of digital transformation in the systems and tools businesses rely on, recent years have yielded transformative approaches to technology that can finally actually change the way people and processes work, rather than just make...

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        Topics: Analytics, Internet of Things, Data, Digital Technology, blockchain, Conversational Computing, collaborative computing, mobile computing, extended reality, AI and Machine Learning

        Organizations universally desire the business outcome of improved organizational agility — in other words, the ability to quickly and effectively identify and respond to business risks and opportunities, typically through workforce-related actions. Being agile requires that an organization be adept at two things: harnessing cognitive assets, the knowledge and ideas that comprise the intellectual capital of a workforce, and deploying and using technologies that channel those assets where they...

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        Topics: Human Capital Management, Learning Management, Collaboration, Workforce Management, Knowledge Management, AI and Machine Learning

        Kinaxis recently held its annual user conference, Kinexions, which focuses on helping the company’s customers improve their execution of supply chain and sales and operations planning (S&OP). Its RapidResponse software handles S&OP, demand, supply, inventory and capacity planning. S&OP is a function sorely in need of improvement: Our research finds that only 22 percent of companies perform it well or very well.

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        Topics: Continuous Planning, Analytics, Enterprise Resource Planning, continuous supply chain, business digital commerce, AI and Machine Learning

        Sage Intacct recently hosted its annual user group meeting, Advantage, and earlier this year met with industry analysts. Both meetings shed light on how the company is addressing two key opportunities. One is building a robust offering to address rapidly evolving technology requirements for the Office of Finance. The other is broadening the scope of its offering to address the financial management and administration needs of its customers.

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        Topics: Office of Finance, business intelligence, Financial Performance Management, ERP and Continuous Accounting, robotic finance, Predictive Planning, revenue and lease accounting, AI and Machine Learning

        Here are some insights on Incentive Solutions drawn from our latest Value Index research, which provides an analytic assessment of how well vendor offerings address buyers’ requirements. The Ventana Research Value Index on Sales Performance Management 2019 is the distillation of a year of market and product research efforts by Ventana Research. We evaluated Incentive Solutions and eight other vendors in seven categories, five product-related adaptability, capability, manageability, reliability...

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        Topics: Sales, Customer Experience, Office of Finance, Analytics, Contact Center, Data, Sales Performance Management, Financial Performance Management, Digital Technology, Digital Commerce, Predictive Planning, Conversational Computing, collaborative computing, mobile computing, Subscription Management, agent management, intelligent sales, AI and Machine Learning

        Here are some insights on NICE drawn from our latest Value Index research, which provides an analytic assessment of how well vendor offerings address buyers’ requirements. The Ventana Research Value Index on Sales Performance Management 2019 is the distillation of a year of market and product research efforts by Ventana Research. We evaluated NICE and eight other vendors in seven categories, five product-related adaptability, capability, manageability, reliability and usability) and two...

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        Topics: Sales, Customer Experience, Mobile Technology, Office of Finance, Analytics, Contact Center, Data, Sales Performance Management, Financial Performance Management, Digital Technology, Digital Commerce, Predictive Planning, Conversational Computing, collaborative computing, Subscription Management, agent management, intelligent sales, AI and Machine Learning

        Here are some insights on beqom drawn from our latest Value Index research, which provides an analytic assessment of how well vendor offerings address buyers’ requirements. The Ventana Research Value Index on Sales Performance Management 2019 is the distillation of a year of market and product research efforts by Ventana Research. We evaluated beqom and eight other vendors in seven categories, five product-related adaptability, capability, manageability, reliability and usability) and two...

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        Topics: Sales, Customer Experience, Office of Finance, Analytics, Contact Center, Data, Sales Performance Management, Financial Performance Management, Digital Technology, Predictive Planning, Conversational Computing, collaborative computing, mobile computing, Subscription Management, agent management, intelligent sales, AI and Machine Learning

        Here are some insights on SAP drawn from our latest Value Index research, which provides an analytic assessment of how well vendor offerings address buyers’ requirements. The Ventana Research Value Index on Sales Performance Management 2019 is the distillation of a year of market and product research efforts by Ventana Research. We evaluated SAP and eight other vendors in seven categories, five product-related adaptability, capability, manageability, reliability and usability) and two...

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        Topics: Sales, Customer Experience, Office of Finance, Analytics, Contact Center, Data, Financial Performance Management (FPM), Sales Performance Management, Digital Technology, Digital Commerce, Predictive Planning, Conversational Computing, collaborative computing, mobile computing, Subscription Management, agent management, intelligent sales, AI and Machine Learning

        Here are some insights on Optymyze drawn from our latest Value Index research, which provides an analytic assessment of how well vendor offerings address buyers’ requirements. The Ventana Research Value Index on Sales Performance Management 2019 is the distillation of a year of market and product research efforts by Ventana Research. We evaluated Optymyze and eight other vendors in seven categories, five product-related adaptability, capability, manageability, reliability and usability) and two...

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        Topics: Sales, Customer Experience, Office of Finance, Analytics, Contact Center, Data, Sales Performance Management, Financial Performance Management, Digital Technology, Digital Commerce, Predictive Planning, Conversational Computing, collaborative computing, mobile computing, Subscription Management, agent management, intelligent sales, AI and Machine Learning

        Here are some insights on Anaplan drawn from our latest Value Index research, which provides an analytic assessment of how well vendor offerings address buyers’ requirements. The Ventana Research Value Index on Sales Performance Management 2019 is the distillation of a year of market and product research efforts by Ventana Research. We evaluated Anaplan and eight other vendors in seven categories, five product-related adaptability, capability, manageability, reliability and usability) and two...

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        Topics: Sales, Customer Experience, Office of Finance, Analytics, Contact Center, Data, Sales Performance Management, Financial Performance Management, Digital Technology, Digital Commerce, Predictive Planning, Conversational Computing, collaborative computing, mobile computing, Subscription Management, agent management, intelligent sales, AI and Machine Learning

        With the backing of Great Hill Partners and Spectrum Equity, the company Varicent Software launched on Jan. 1st, purchasing IBM’s Sales Performance Management (SPM) assets and hiring employees from IBM’s SPM group. They will join a new team that includes Varicent’s original founders and key leadership.

        This set of insights is drawn from our latest Value Index research, which provides an analytic assessment of how well vendor offerings address buyers’ requirements. The Ventana Research Value...

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        Topics: Sales, Customer Experience, Office of Finance, Analytics, Contact Center, Data, Sales Performance Management, Financial Performance Management, Digital Technology, Digital Commerce, Predictive Planning, Conversational Computing, collaborative computing, mobile computing, Subscription Management, agent management, intelligent sales, AI and Machine Learning

        Here are some insights on Xactly drawn from our latest Value Index research, which provides an analytic assessment of how well vendor offerings address buyers’ requirements. The Ventana Research Value Index on Sales Performance Management 2019 is the distillation of a year of market and product research efforts by Ventana Research. We evaluated Xactly and eight other vendors in seven categories, five product-related adaptability, capability, manageability, reliability and usability) and two...

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        Topics: Sales, Customer Experience, Office of Finance, Analytics, Contact Center, Data, Sales Performance Management, Financial Performance Management, Digital Technology, Digital Commerce, Predictive Planning, Conversational Computing, collaborative computing, mobile computing, Subscription Management, agent management, intelligent sales, AI and Machine Learning

        For years I’ve viewed with skepticism the claim that one technology or another will reduce audit costs. For one, there’s rarely a silver bullet. An array of moving parts drive audit fees. For example, the complexity of the corporation, accounting data management and the audit staff’s familiarity with the industry and the company all affect the time auditors must spend. Also, most of the time I’ve found that achieving significant savings was not the result of going from good to great, but from...

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        Topics: Office of Finance, Analytics, Business Intelligence, Financial Performance Management, ERP and Continuous Accounting, robotic finance, AI and Machine Learning

        Here are some insights on Oracle drawn from our latest Value Index research, which provides an analytic assessment of how well vendor offerings address buyers’ requirements. The Ventana Research Value Index on Sales Performance Management 2019 is the distillation of a year of market and product research efforts by Ventana Research. We evaluated Oracle and eight other vendors in seven categories, five product-related adaptability, capability, manageability, reliability and usability) and two...

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        Topics: Sales, Customer Experience, Contact Center, Data, Sales Performance Management, Sales Performance Management (SPM), Digital Technology, Digital Commerce, Predictive Planning, Conversational Computing, collaborative computing, mobile computing, Subscription Management, agent management, intelligent sales, AI and Machine Learning

        For interactions with customers to go well, organizations must manage an ever-increasing array of engagement channels. Our research finds that organizations expect to see interaction volumes increase on all channels, especially digital ones such as text-based messaging, chat, mobile and social apps. Unfortunately, the systems that manage these channels are typically disparate and uncoordinated and may not use the same underlying technology. This makes it difficult for organizations to...

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        Topics: Customer Experience, Voice of the Customer, business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Internet of Things, Contact Center, Data, Digital Technology, Digital Commerce, blockchain, natural language processing, data lakes, Intelligent CX, Subscription Management, agent management, extended reality, AI and Machine Learning

        Using customer analytics effectively involves several challenges. Organizations must make it a business priority, cultivate leadership and set a course for ensuring data and analytics are being processed and governed effectively. But effectiveness also requires technology that will assist in the effective operations and management of customers and help an organization achieve its goals.

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        Topics: Customer Experience, Voice of the Customer, embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Contact Center, Data, Digital Technology, Digital Commerce, blockchain, natural language processing, data lakes, Intelligent CX, Conversational Computing, collaborative computing, mobile computing, Subscription Management, agent management, extended reality, AI and Machine Learning

        I am happy to share some insights from our latest Value Index research, which rates how well vendors’ offerings meet buyers’ requirements in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). The Ventana Research Value Index: Sales Performance Management 2019 is the distillation of a year of market and product research efforts by Ventana Research. Drawing on our...

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        Topics: Sales, Customer Experience, Office of Finance, Analytics, Contact Center, Data, Sales Performance Management, Financial Performance Management, Digital Technology, Digital Commerce, Predictive Planning, Conversational Computing, collaborative computing, mobile computing, Subscription Management, agent management, intelligent sales, AI and Machine Learning

        Customer analytics have never been more important, but effectively creating and managing them is not easy. The data that’s required to achieve visibility into all customer activity involves many applications and systems and it’s a challenge to ensure the data used is accurate and consistent. Even once data is assembled, organizations often struggle to apply analytics to create the metrics that best represent an understanding of the past and, more importantly, the path to the future.

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        Topics: Customer Experience, Voice of the Customer, embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Lake, Data Preparation, Information Management, Contact Center, Data, Digital Technology, Digital Commerce, blockchain, natural language processing, Intelligent CX, Conversational Computing, collaborative computing, Subscription Management, agent management, extended reality, AI and Machine Learning

        Ensuring that the sales organization contributes as fully as possible to the success of the organization — to revenue, growth, prof itability and the overall customer experience — requires not only dedication but effective strategy and planning. A well-developed strategy and plan to utilize current and future sales talent is essential for the best possible sales performance. To carry out this mission, organizations need a set of coordinated sales-related activities, processes and systems that...

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        Topics: Sales, Customer Experience, Office of Finance, Analytics, Contact Center, Data, Sales Performance Management, Financial Performance Management, Digital Technology, Digital Commerce, Predictive Planning, Conversational Computing, collaborative computing, mobile computing, Subscription Management, agent management, intelligent sales, AI and Machine Learning

        Today’s intense competition requires that companies know as much as they can about their customers in order to anticipate their needs and deliver a superior customer experience. However, many organizations struggle to do this well. Implementing initiatives to improve customer value across any department or process involving customers requires both in-depth visibility into current operations and excellent metrics.

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        Topics: Customer Experience, Voice of the Customer, business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Internet of Things, Contact Center, Data, Digital Commerce, blockchain, natural language processing, data lakes, Intelligent CX, Conversational Computing, collaborative computing, mobile computing, Subscription Management, agent management, extended reality, AI and Machine Learning

        The traditional office of finance has five main organs: accounting keeps the books; financial planning and analysis (FP&A) analyzes performance and manages the forward-looking activities of the company such as planning, budgeting and forecasting; corporate finance raises outside money; treasury takes care of the cash and bank accounts, and tax. The modern office of finance requires a sixth: Finance IT (FIT).

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        Topics: Office of Finance, Analytics, Financial Performance Management, Price and Revenue Management, Digital Technology, Operations & Supply Chain, ERP and Continuous Accounting, blockchain, robotic finance, Predictive Planning, Conversational Computing, revenue and lease accounting, collaborative computing, Subscription Management, AI and Machine Learning

        Having effective analytics enables businesses to understand far better than ever before the data they’re collecting, and to do so in greater volumes and more forms. These new capabilities are especially relevant to sales organizations. When applied to sales data, analytics can help sales teams achieve quotas and forecast more consistently, as well as understand the impacts of incentives and maximize the potential of territories, all of which help improve sales performance. These benefits...

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        Topics: Customer Experience, Voice of the Customer, business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Internet of Things, Contact Center, Data, Digital Technology, Digital Commerce, blockchain, natural language processing, data lakes, Intelligent CX, Subscription Management, agent management, AI and Machine Learning

        By itself, data isn’t useful for business; the application of analytics is necessary to transform data into actionable information. Data analysis of one sort or another has long been a core competence of finance departments, applied to balance sheets, income statements or cash flow statements. Today, however, Finance must go beyond these basics by expanding the scope of the data being examined to include all financial and operational information that can yield actionable insights. Analysis thus...

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        Topics: Customer Experience, Human Capital Management, Voice of the Customer, embedded analytics, Learning Management, Analytics, Business Intelligence, Collaboration, Data Governance, Data Lake, Data Preparation, Information Management, Internet of Things, Contact Center, Data, Product Information Management, Sales Performance Management, Workforce Management, Financial Performance Management, Price and Revenue Management, Digital Technology, Digital Marketing, Digital Commerce, ERP and Continuous Accounting, blockchain, natural language processing, robotic finance, Predictive Planning, candidate engagement, Intelligent CX, Conversational Computing, Continuous Payroll, revenue and lease accounting, collaborative computing, mobile computing, Subscription Management, total rewards management, intelligent marketing, intelligent sales, AI and Machine Learning

        Organizations’ use of data and information is evolving as the amount of data and the frequency with which that data is collected increase. Data now streams into organizations from myriad sources, among them social media feeds and internet-of-things devices. These seemingly ever-increasing volumes of devices and data streams offer both challenges and opportunities to capture information about a business and improve its operations.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Lake, Information Management, Internet of Things, Data, Digital Technology, AI and Machine Learning

        It’s no secret that employees are overwhelmed. They’re having to use an array of systems and enterprise tools in the flow of work and deal with an explosion of email messages and other communications requiring some response or action and mountains of content to consume and retain. On top of these time demands, employees must try to keep up with a staggering amount of organizational change.

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        Topics: Human Capital Management, business intelligence, Learning Management, Information Management, Workforce Management, Digital Technology, natural language processing, AI and Machine Learning

        The emerging internet of things (IoT) is an extension of digital connectivity to devices and sensors in homes, businesses, vehicles and potentially almost anywhere. This innovation means that virtually any appropriately designed device can generate and transmit data about its operations, which can facilitate monitoring and a range of automatic functions. To do this IoT requires a set of event-centered information and analytic processes that enable people to use that event information to make...

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Internet of Things, Data, Information Management (IM), Digital Technology, data lakes, AI and Machine Learning

        Organizations now must store, process and use data of significantly greater volume and variety than in the past. These factors plus the velocity of data today — the unrelentingly rapid rate at which it is generated, both in enterprise systems and on the internet — add to the challenge of getting the data into a form that can be used for business tasks.

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        Topics: Analytics, Business Intelligence, Data Governance, Data Preparation, Information Management, Internet of Things, Data, Digital Technology, blockchain, data lakes, AI and Machine Learning
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